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[100% OFF] Deep Learning Course with Flutter & Python - Build 6 AI Apps Free

Join the most comprehensive Flutter & Deep Learning course on Udemy and learn how to build amazing state-of-the-art Deep Learning applications! Do you want to learn about State-of-the-art Deep Learning algorithms and how to apply them to IOS/Android apps? Then this course is exactly for you! You will learn how to apply various State-of-the-art Deep Learning algorithms such as GAN's, CNN's, & Natural Language Processing. In this course, we will build 6 Deep Learning apps that will demonstrate the tools and skills used in order to build scalable, State-of-the-Art Deep Learning Flutter applications! After completing this course you will be able to: Learn the tools and skills to develop any AI idea you have onto a mobile phone. Have a clear understanding of different types of Neural Networks and how you can use them to your advantage. Build any Neural Networks in Python and then export them into your Flutter application. Use different strategies to get neural networks with 90%+ accuracy. Why should you choose this course? This course covers all the steps that one should take to create a Flutter application that uses State-of-the-Art Deep Learning approaches. It is extremely hard to find good tutorials that teach you how to implement these algorithms, so the instructor, Samuel Boylan-Sajous, who has been programming for years, and has a Computer Science degree at the University of Guelph, has decided to share all of his knowledge with other students that are passionate about Deep Learning and building practical A.I. applications. Here's what's included in the course: Building a neural network on Teachable Machine and exporting it into Flutter project Building a neural network in Keras/Python on Google Collab/Jupyter Notebook and exporting it into Flutter project Using API's to perform some Natural Language Processing and implementing those algorithms into our app. Build a GAN in python and implement it into your flutter application. And much more! This course is for you if ... You're interested in building real native mobile apps for the two most popular mobile platforms - iOS and Android You're passionate about Deep Learning/AI or Mobile Development and want to expand your knowledge. You want to expand your Deep Learning/AI portfolio with 6 Cutting Edge Deep Learning apps! Want to learn State-of-the-Art Deep Learning algorithms and how you can use them on a mobile device! Course prerequisites: Knowing mobile development will help a lot but is not a hard requirement (You would be fine if you only knew CSS/HTML & Object-Oriented Programming, just do some research on what Flutter is) Know some theory behind Neural Networks (Know how data is processed in a Neural Network) Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content or anything related to any topic, you can always post a question in the course or send us a direct message.

[100% OFF] How to build successful project strategy Free

You're in the right place. You can learn through t... Morehis course how to start, build and implement successful project strategy. You will get advice how to measure and follow-up your project strategy. This will certainly make your current or coming project successful from the beginning. This course will help you 1. Understand project strategy principles 2. Start your project strategy from zero, linked to enterprise expectation 3. Build successful project strategy according to planned objectives 4. Implement planned and selected strategy into practice 5. Measure your success, recognize problems before failure 6. Avoid mistakes from start until end. Have you had problems in your project scope, schedule or budget? Have you ever thought there could be better ways to success in projects? Enroll this course to learn more, be more successful and take your projects into next level. It's important to understand both enterprise and project KPIs (Key Performance Indicators) and how they link to each other for expected outcomes. Project management is a function which will glue together many departments, teams and people for desired outcome. To make your project successful it needs to be strategic. This course is designed for beginners and more advance project managers or project members. It will also help stakeholders like sponsors to understand how projects fail or success. You can take tips and tricks from this course into your toolbox and create a success! Enroll today! Who this course is for: Project team members Project managers Project sponsors/other stakeholders Less
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[100% OFF] Decision Trees, Random Forests, AdaBoost & XGBoost in Python Free

You're looking for a complete Decision tree course... More that teaches you everything you need to create a Decision tree/ Random Forest/ XGBoost model in Python, right? You've found the right Decision Trees and tree based advanced techniques course! After completing this course you will be able to: Identify the business problem which can be solved using Decision tree/ Random Forest/ XGBoost of Machine Learning. Have a clear understanding of Advanced Decision tree based algorithms such as Random Forest, Bagging, AdaBoost and XGBoost Create a tree based (Decision tree, Random Forest, Bagging, AdaBoost and XGBoost) model in Python and analyze its result. Confidently practice, discuss and understand Machine Learning concepts How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Decision tree, Random Forest, Bagging, AdaBoost and XGBoost. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through Decision tree. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a decision tree based model, which are some of the most popular Machine Learning model, to solve business problems. Below are the course contents of this course on Linear Regression: Section 1 - Introduction to Machine Learning In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model. Section 2 - Python basic This section gets you started with Python. This section will help you set up the python and Jupyter environment on your system and it'll teach you how to perform some basic operations in Python. We will understand the importance of different libraries such as Numpy, Pandas & Seaborn. Section 3 - Pre-processing and Simple Decision trees In this section you will learn what actions you need to take to prepare it for the analysis, these steps are very important for creating a meaningful. In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split. In the end we will create and plot a simple Regression decision tree. Section 4 - Simple Classification Tree This section we will expand our knowledge of regression Decision tree to classification trees, we will also learn how to create a classification tree in Python Section 5, 6 and 7 - Ensemble technique In this section we will start our discussion about advanced ensemble techniques for Decision trees. Ensembles techniques are used to improve the stability and accuracy of machine learning algorithms. In this course we will discuss Random Forest, Baggind, Gradient Boosting, AdaBoost and XGBoost. By the end of this course, your confidence in creating a Decision tree model in Python will soar. You'll have a thorough understanding of how to use Decision tree modelling to create predictive models and solve business problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 4 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the Python environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in Python Understanding of Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture where we actually run each query with you. Why use Python for data Machine Learning? Understanding Python is one of the valuable skills needed for a career in Machine Learning. Though it hasn’t always been, Python is the programming language of choice for data science. Here’s a brief history: In 2016, it overtook R on Kaggle, the premier platform for data science competitions. In 2017, it overtook R on KDNuggets’s annual poll of data scientists’ most used tools. In 2018, 66% of data scientists reported using Python daily, making it the number one tool for analytics professionals. Machine Learning experts expect this trend to continue with increasing development in the Python ecosystem. And while your journey to learn Python programming may be just beginning, it’s nice to know that employment opportunities are abundant (and growing) as well. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Anyone curious to master Decision Tree technique from Beginner to Advanced in short span of time Less
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[100% OFF] The Complete Android App Development Masterclass: Build Apps Free

Welcome To The Complete Android App Development Ma... Moresterclass: Build 4 Apps ⇉ Join 500,000+ Students Who Have Enrolled in Our Udemy Courses! ⇉ 10,000+ Five Star Reviews Show Students Who Enrolling Are Getting Real Results! ⇉ You Get Over 20+ hours and 100+ Lectures of FULL HD content! ⇉ Watch the Promo Video to see how you can Get Started Today! _________________________________________________________________________ Here are all of the benefits to enrolling in our complete Android App course today -We've designed this course to include everything you need to know about Android App Development in 2020 and beyond.. -We've also designed this course so that you can learn everything you need to start building your own Android Apps in less than 8 weeks.. -Our previous android app course had more than 100,000 students -- so we've made this course bigger, better, with more apps and even more affordable -Don't have any previous experience with Android App Development? No problem. We take you from beginner to advanced and show you how to get build real world android apps from scratch - you don't need any prior experience to enroll in our course. But thats not all... We believe the best way to learn in by DOING. That is why we have you build 4 real world applications right along side of us in this course! These hands on projects will allow you to not only learn by watching, but by DOING as well. Here are some of the projects you will create in our complete after effects cc master class First you will build a sample application (add in more about these and the other projects) Here are all of the Useful Skills you will learn in our complete course: Java Language Designing reach User Interfaces Debugging android applications YouTube and Google Maps APIs Databases Content Providers Networking in Android Handling Background Tasks Notifications Version control with Git and GitHub Tips for Publishing So much more _________________________________________________________________________ With the right mindset, understanding, and application, you will instantly begin learning how to become a professional android app developer from scratch. When we learn something new - we add it to the course - at no additional cost to you! This is a course that will continue to add more and more to every aspect of your life. _________________________________________________________________________ What I can't do in this Course.. I can't guarantee your success – this course does take work on your part. But it can be done! I am also not responsible for your actions. You are responsible for 100% of the decisions and actions you make while using this course. _________________________________________________________________________ It's time to take action! This course will not remain this price forever! Enroll Today! Every hour you delay is costing you money... See you in the course! Sincerely, Meisam & Joe Less
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[100% OFF] The Complete Front-End Web Development Course! Free

If you would like to get started as a front-end we... Moreb developer, you are going to LOVE this course! Work on projects ranging from a simple HTML page to a complete JavaScript based Google Chrome extension. We will cover the following technologies in this course: Web development basics with HTML Cascading Style Sheets (CSS) JavaScript programming jQuery JavaScript library Bootstrap framework We will work on 3 class projects throughout this course: Simple text site - We will use what we learned in the HTML sections to create a simple text site. This project will help you learn HTML structure and the essential elements. Fallout inspired Pip-Boy - We will take what we learned in the CSS and Bootstrap sections of the course to code a Pip-Boy from the game Fallout. This project will help you learn the design elements of modern web development. Google Chrome extension - We will finish the course by programming a JavaScript based Google Chrome extension. This project will help you understand the logical parts of web development. This course covers the most popular web development frameworks, and will get you started on your path towards becoming a full-stack web developer! Still not sold? Check out a few of the awesome reviews this course has received! "Excellent Course! Highly Recommend It! Such a great hands on experience with this course." "Very nice course, covers all the stuff you need, good voice and good explanation makes it perfect for people that are new to HTML. Also there's some best practices recommendations which are useful even for advanced developers." "Excellence in giving the optimal set of tools for web development beginners seeking a well-rounded start for professional web development." Thank you for taking the time to read this, and we hope to see you in the course! Who this course is for: Anyone who would like to learn front-end web development Less
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[100% OFF] ML for Business Managers: Build Regression model in R Studio Free

You're looking for a complete Linear Regression co... Moreurse that teaches you everything you need to create a Linear Regression model in R, right? You've found the right Linear Regression course! After completing this course you will be able to: · Identify the business problem which can be solved using linear regression technique of Machine Learning. · Create a linear regression model in R and analyze its result. · Confidently practice, discuss and understand Machine Learning concepts A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course. How this course will help you? If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular technique of machine learning, which is Linear Regression Why should you choose this course? This course covers all the steps that one should take while solving a business problem through linear regression. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. Below are the course contents of this course on Linear Regression: · Section 1 - Basics of Statistics This section is divided into five different lectures starting from types of data then types of statistics then graphical representations to describe the data and then a lecture on measures of center like mean median and mode and lastly measures of dispersion like range and standard deviation · Section 2 - R basic This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R. · Section 3 - Introduction to Machine Learning In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model. · Section 4 - Data Preprocessing In this section you will learn what actions you need to take a step by step to get the data and then prepare it for the analysis these steps are very important. We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bi-variate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation and correlation. · Section 5 - Regression Model This section starts with simple linear regression and then covers multiple linear regression. We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures. We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results, what are other variations to the ordinary least squared method and how do we finally interpret the result to find out the answer to a business problem. By the end of this course, your confidence in creating a regression model in R will soar. You'll have a thorough understanding of how to use regression modelling to create predictive models and solve business problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What is the Linear regression technique of Machine learning? Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value. Linear regression is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y). More specifically, that y can be calculated from a linear combination of the input variables (x). When there is a single input variable (x), the method is referred to as simple linear regression. When there are multiple input variables, the method is known as multiple linear regression. Why learn Linear regression technique of Machine learning? There are four reasons to learn Linear regression technique of Machine learning: 1. Linear Regression is the most popular machine learning technique 2. Linear Regression has fairly good prediction accuracy 3. Linear Regression is simple to implement and easy to interpret 4. It gives you a firm base to start learning other advanced techniques of Machine Learning How much time does it take to learn Linear regression technique of machine learning? Linear Regression is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn Linear regression starts from the basics and takes you to advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to remember whatever you have learnt. Therefore, we have also provided you with another data set to work on as a separate project of Linear regression. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 4 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the R environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in R Understanding of Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture in R where we actually run each query with you. Why use R for data Machine Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Anyone curious to master Linear Regression from beginner to advanced in short span of time Less
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[100% OFF] The Complete PHP 7 Guide for Web Developers Free

PHP levels up! The world’s favorite back-end pro... Moregramming language now gets a new version packed with new features and significant upgrades. PHP is touted as the de facto language for server-side scripting in app development and even websites. The popularity of the language has also made it extremely useful as a general-purpose programming language. The latest version gets a huge boost in terms of performance, speed, new scalar type declarations and even a new operator. The performance and speed boost comes from the new turbocharged Zend Engine 3, which also allows PHP7 to consume half as much as memory as PHP5 and support more component users at the same time. In addition the new engine, other changes to PHP7 include replacing fatal- or recoverable-level legacy PHP error mechanisms with object-oriented exceptions, inclusion of left-hand-side expressions, unmaintained or deprecated server application programming interfaces (SAPIs) were removed, list() operator now includes support for strings, new language features such as return type declarations for functions, and support for the scalar types in return type and parameter declarations. With so much power under the hood, it is no wonder a lot of developers are shifting to PHP7. With this course, you too can learn how to supercharge your apps and websites. Our complete PHP 7 guide is the perfect course to get you started with the amazing features included into the already powerful programming language. It comes loaded with everything you need to know to upgrade to the fancy new iteration. The course will cover not only the fundamentals of PHP 5, but will also familiarize you with the new features and changes in PHP 7. These new additions may not seem like much, but they will improve your coding by four fold, especially ones such as unserialise function (which will accept another optional parameter) and password hash function (that now automatically generates a secure salt, rather than accept a given salt). The PHP 7 tutorial also includes breaking down features such as the new spaceship operator, Throwable Interface, Handling Fatal Errors, Generator Delegation, Anonymous Classes, Fetching Data & Error Handling and so much more. That’s not all. Some sections even includes quizzes to help you test your understanding and a project that will allow you to become comfortable coding in PHP 7. In this course, you will learn: Introduction to PHP, its fundamentals and its environment What is new in PHP 7 and how it differs from PHP 5 New features such as spaceship operators, error handling, new declarations, new classes, new functions, etc. Fully design a GoodQuotes app project that will allow you to add, edit and remove data Less
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[100% OFF] Data Science: Supervised Machine Learning Bootcamp in Python Free

This course focuses on one of the main branches of... More Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising the Python Libraries will train you enough and will make you comfortable with the programming language. The course is divided into two sections, in the first section, you will be having lectures about Python and the fundamental libraries like Numpy, Pandas, Seaborn, Scikit-Learn and Tensorflow that are necessary for one to be familiar with before putting his hands-on Supervised Machine Learning. Then is the Supervised Learning part, which basically comprises three main chapters Regression, Classification, and Deep Learning, each chapter is thoroughly explained, both theoretically and experimentally. During all of these lectures, we’ll be learning how to use the different machine learning algorithms to create some mind-blowing modules of Machine Learning, and at the end of the course, you’ll be trained enough that you would be able to develop you own Recognitions Systems and Prediction Models and many more. Let's get started! Who this course is for: Those who are interested in AI and Machine Learning Those who have basic knowledge of any programming language Those who want to be create awesome Machine Learning and AI modules And those who want to earn some handsome amount of money from Machine Learning Field in Future Less
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[100% OFF] The DevOps Way - A School for Mastering DevOps Free

A practitioner's guide to understanding DevOps inc... More. DevOps Culture, Engineering, CI/CD, DevSecOps & Enterprise DevOps Less
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[100% OFF] Complete Machine Learning with R Studio - ML for 2020 Free

You're looking for a complete Machine Learning cou... Morerse that can help you launch a flourishing career in the field of Data Science & Machine Learning, right? You've found the right Machine Learning course! After completing this course you will be able to: · Confidently build predictive Machine Learning models to solve business problems and create business strategy · Answer Machine Learning related interview questions · Participate and perform in online Data Analytics competitions such as Kaggle competitions Check out the table of contents below to see what all Machine Learning models you are going to learn. How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular techniques of machine learning. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through linear regression. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 3 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the Python environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in Python Understanding of models - Fifth and sixth section cover Classification models and with each theory lecture comes a corresponding practical lecture where we actually run each query with you. Why use R for Machine Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Less
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[100% OFF] Socket Programming in Python | Socket Programming Course Free

Welcome to this course on Python Socket Programmin... Moreg Tutorial. In this video we will see the Basics of Networking. The goal of this Socket programming tutorial is to learn how to build client/server applications that communicate using sockets. We are going to look at a bunch of application level protocols (HTTP, DNS, FTP, SMTP, POP, IMAP, ..). The Objective of this course is to understand principles of networking, learn TCP and UDP features, learn to implement Python programs to access networking functionality. We will see Python examples of client and server program structures etc. In this Course you will learn Basics of Networking, Basics of Sockets | What is a Socket?, Write Your First Socket Program using Python socket module, TCP/IP Client and Server, Build a Python Socket Client with Example, UDP Client/Server Socket in Python with Example, Make a Multithreaded Socket Server, Socket Server with Multiple Clients Less
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89 used

[10$] Cloud Computing for Machine Learning

Build and Deploy Machine Learning programs on the cloud
Expired
107 used

[100% OFF] Deep Learning Course with Flutter & Python - Build 6 AI Apps Free

Join the most comprehensive Flutter & Deep Lea... Morerning course on Udemy and learn how to build amazing state-of-the-art Deep Learning applications! Do you want to learn about State-of-the-art Deep Learning algorithms and how to apply them to IOS/Android apps? Then this course is exactly for you! You will learn how to apply various State-of-the-art Deep Learning algorithms such as GAN's, CNN's, & Natural Language Processing. In this course, we will build 6 Deep Learning apps that will demonstrate the tools and skills used in order to build scalable, State-of-the-Art Deep Learning Flutter applications! After completing this course you will be able to: Learn the tools and skills to develop any AI idea you have onto a mobile phone. Have a clear understanding of different types of Neural Networks and how you can use them to your advantage. Build any Neural Networks in Python and then export them into your Flutter application. Use different strategies to get neural networks with 90%+ accuracy. Why should you choose this course? This course covers all the steps that one should take to create a Flutter application that uses State-of-the-Art Deep Learning approaches. It is extremely hard to find good tutorials that teach you how to implement these algorithms, so the instructor, Samuel Boylan-Sajous, who has been programming for years, and has a Computer Science degree at the University of Guelph, has decided to share all of his knowledge with other students that are passionate about Deep Learning and building practical A.I. applications. Here's what's included in the course: Building a neural network on Teachable Machine and exporting it into Flutter project Building a neural network in Keras/Python on Google Collab/Jupyter Notebook and exporting it into Flutter project Using API's to perform some Natural Language Processing and implementing those algorithms into our app. Build a GAN in python and implement it into your flutter application. And much more! This course is for you if ... You're interested in building real native mobile apps for the two most popular mobile platforms - iOS and Android You're passionate about Deep Learning/AI or Mobile Development and want to expand your knowledge. You want to expand your Deep Learning/AI portfolio with 6 Cutting Edge Deep Learning apps! Want to learn State-of-the-Art Deep Learning algorithms and how you can use them on a mobile device! Course prerequisites: Knowing mobile development will help a lot but is not a hard requirement (You would be fine if you only knew CSS/HTML & Object-Oriented Programming, just do some research on what Flutter is) Know some theory behind Neural Networks (Know how data is processed in a Neural Network) Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content or anything related to any topic, you can always post a question in the course or send us a direct message. Less
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[100% OFF] The Complete Typescript for Beginners From Zero To Hero 2020 Free

Every other course online teaches you the basic sy... Morentax and features of Typescript, but only this course will show you how to apply Typescript on real projects, instructing you how to build large, successful projects through example. Typescript is a 'super-set' of Javascript. That means that if you already know Javascript, you are ready to take this course. Typescript adds in several important features to Javascript, including a type system. This type system is designed to help you catch errors during development, rather than when you are running your code. That means you'll be twice as productive by catching bugs earlier in development. But besides the type system, Typescript also provides several tools for structuring large codebases and writing truly reusable code. ES6 is the 6th edition, officially known as ECMAScript 2015, and was finalised in June 2015. ES6 adds significant new syntax for writing complex applications, including classes and modules, but defines them semantically in the same terms as ECMAScript 5 strict mode. Browser support for ES6 is still incomplete. However, ES6 code can be transpiled into ES5 code, which has more consistent support across browsers. Typescript is a superset of Javascript that compiles to plain Javascript. It is also the main language used for Angular 2. ES6 | ES2015 | Typescript | ES6 Tutorial | ES2015 Tutorial | Typescript Tutorial | ES6 Tutorial for Beginners | ES2015 Tutorial for Beginners | Typescript tutorial for Beginners Less
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106 used

[100% OFF] PHP MySQL & CodeIgniter: Complete Guide Free

In this PHP MySQL & CodeIgniter: Complete Guid... Moree course you will learn how to build Dynamic web applications from scratch. We will cover everything from PHP core concepts to CodeIgniter web app development. In the entire course first you will learn complete PHP & MySQL in-depth and we will build a EMS (Employee Management System) CRUD based web application. Once we are done with the PHP & MySQL project we will then build the same project with OOP (Object Oriented Programming). To be more specific we will learn about MVC (Model View Controller) and how it works in CodeIgniter Framework. This will help you build EMS Web App in a much more easier way in CodeIgniter framework. Who this course is for: Anyone who wants to learn web development Anyone who wants to learn PHP & MySQL Anyone who wants to learn CodeIgniter framework Anyone who wants to build their own web application Anyone who wants to improve their skills in PHP & MySQL or CodeIgniter Less
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46 used

[100% OFF] The Complete 2020 PHP Full Stack Web Developer Bootcamp Free

Do you want to be a Certified Web Developer? or... More Are you are a student and want to get a Job as Web Developer? or Do you want be Freelancer to earn an extra part time income? or You want to improve your Web Development Skills at Work? If these are your goals then this course is exactly made for you to Become PHP Full Stack Web Developer! 48+ hours of course content with Exercises, Quiz, Assignments and Projects. If you give your valuable time to this course and I will promise to help you achieve your goal. RIGHT AFTER THIS COURSE, YOU WILL BE: Able to Build websites. Get a job as a junior web developer. Start your own online business with WordPress. Become Freelancer Web developer on Fiverr or UpWork. Be proficient with databases and server-side languages with PHP and MySQL. Become a front-end and Back-end developer - Complete Full Stack Developer. In less than 30 days, you'll be ready for an entry-level job as a Full Stack Web Developer. This course will give you the following Skills: Front End Web Development: HTML. CSS. JAVASCRIPT. BOOTSTRAP. Back End Web Development: PHP. MYSQL. WORDPRESS. PHP OOP. BASICS: WEB BASICS. INTRODUCTION TO XML. COMPLETE UNDERSTANDING OF JSON. INTRODUCTION TO REST AND API. SOFT SKILLS: INTERVIEW QUESTIONS. PHP RESUME. STUDENT MENTORSHIP. PROJECTS: PHPKart - Complete Shopping Cart Website using HTML, CSS, JAVASCRIPT, PHP and MySQL. LearnWP.xyz - Blogging Website with WordPress. (Buy Domain, Web Hosting, Installing Themes and etc...) CERTIFICATION PROVIDED: Get your PHP Full Stack Developer Certification. VALUABLE RESOURCES: You will become PHP Full Stack Web Developer: 48+ hours of course. - Worth $199 You will be Certified PHP Full Stack Web Developer - Worth $399 Complete Source Code and Projects: PHPKart & LearnWP.xyz - Worth $299 Student Mentorship via Private Facebook Group. - Worth $219 PHP Projects Downloads. - Worth $129 Resume and Interview Questions. - Worth $79 Lifetime Documentation Site Access - Worth $29.90 30 Days Money Back Policy. Total Worth: $1353 FEEDBACK FROM STUDENTS: -> Amazing, above expectations! - Adeel Nazim -> I think , someone who wants to learn php , should start with this course.Great content , so much valuable info in this course , thank you!! - Andreas -> good course with lot of examples. this is the best course in PHP - Murali Krishna Nistala -> This course is very good introduction to PHP. Many examples and every lection has a test and a quiz. - Milan Švarc -> Very easy to understand, lots of examples. Repeats important points in different ways making difficult concepts easier to grasp. - Laura Long -> A well organized course, explained each and every concept in very easy way, now feeling confident while using PHP oop.- Wasim Tamboli -> This course is a easy to learn. and your teaching way is awesome. - Bharat Kumar -> He is explaining the concepts crystal clear . Very thankfull to the teacher - Ponmurali Jeyaprakasam -> Very easy to understand and the best part is there are too many assignments for working which makes u perfect - Gokul Singh Do not miss the Premium Contents with this course: 48+ hours of Full Stack Web Development Course. One Course Covers - 12 Courses: HTML, CSS, JAVASCRIPT, BOOTSTRAP, PHP, MYSQL, PHP OOP, WORDPRESS, XML, API, JSON and REST. 6 Web Development Books for FREE. (1200+ pages long) - Selling for $20 on Amazon Lifetime FREE Access to Premium Bootcamp Documentation Website. - Sold monthly membership PHPKart and LearnWP Website Source Code. - Sold my source code for each $299 Interview Questions (1000+ questions) - Selling for $20 on Amazon 30 days Money Back Guarantee (0% Risk) 100% FREE for Lifetime Access. IF YOU ARE REALLY SERIOUS TO LEARN WEB DEVELOPMENT AND LOOKING FOR THE RIGHT COURSE... THEN THIS IS THE BEST COURSE THAT CAN HELP YOU ACHIEVE YOUR GOAL.. BELIEVE ME, YOU ARE JUST ONE COURSE AWAY FROM BECOMING BRILLIANT WEB DEVELOPER.... Who this course is for: Anyone who wants to learn to code Anyone who wants to generate new income streams Anyone who wants to build websites Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Less
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177 used

[100% OFF ] HANDS ON DOCKER for JAVA Developers Free

This course is a 100% HANDS ON course for Java Ent... Morehusiasts who want to use DOCKER To Build->Ship->Run Java Apps using Docker and want to learn thru 10+ real world hands on use cases. This course is optimized for the busy professional with real world use cases examples and problem solving. The student registering for the course should be able to dedicate time towards Hands on labs to get a clearer understanding on how to use docker. Docker Version: 18.03.1-ce, JDK 8 Learn to build real world apps using Java and Docker with Microservices using the Spring framework, JQuery, Bootstrap and much more.... T Apart from the theoretical aspect here are the HANDS ON LAB Exercises which will be covered MICROSERVICES using Docker . Build a Spring MVC and MYSQL RESTFUL MICROSERVICE, Scale a micro service with multiple containers Build a Proxy Servlet, a filter with a Spring MVC app backed by MYSQL to load balance the requests between containers. Learn what the real world problems are and how Docker attempts to solve real world use cases. Learn to Run WEB Apps on Apache HTTP and NGINX Web servers in Docker as containers. Learn to run Simple Java Programs developed using JDK8 using Docker Create a sample Spring MVC Web App running with a bootstrap and JQUERY UI and run it using Docker Learn about Docker machines and Docker compose Upload your code to DOCKER HUB and share your Docker images for deployments with peers Less
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47 used

[100% OFF] Digital Marketing (SEO, Google Ads, Google Analytics etc) Free

Although this course is for beginners, the knowled... Morege it provides is really advanced. It is full of tips and tricks as well as tested methods that will make you an expert in digital marketing and online advertising. Its curiculim includes: Blogging Social Media Google Ads SEO Google Analytics E-commerce Optimization Conversion Optimization Each section of the course is a step by step guide that not only gives you usefull instructions about the topic it addresses but also tried methods that you can easily use to bring profits to your business and to be a successful digital marketing professional. Less
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129 used

[100% OFF] Fundamentals of Machine Learning[Hindi] Free

This course is designed to understand basic Concep... Moret of Machine Learning. Anyone can opt for this course. No prior understanding of Machine Learning is required. Data pre processing and Simple Linear Regression Concepts are covered in detail. Coding part is not covered, however wherever possible I have attached the code in the resources. Now question is why this course? This Course will not only teach you the basics of Machine learning and Simple Linear Regression. It will also cover in depth mathematical explanation of Cost function and use of Gradient Descent for Simple Linear Regression. Understanding these is must for a solid foundation before entering into Machine Learning World. This foundation will help you to understand all other algorithms and mathematics behind it. Less
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125 used, 100% success rate

[100% OFF] Learn Angular 7 Boilerplate In Hindi (Get A CRUD Project) Free

Description This short course is designed to begi... Morenners having little idea of web applications and is based on a boilerplate project created by Angular 7 CLI. It introduces the versions of AngularJS to Angular2+. It also demonstrates the installation process to the first run of the app. Next, it tries to explain the folder structure and code from file to file. Who this course is for: Beginner in Angular and Node js from Hindi/Urdu speaking background Less
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70 used

[100% OFF] Data Structures And Algorithms In The C Programming Language Free

Have you already got some experience in the C prog... Moreramming language but want to take it further? Then this course is for you. This course will teach you all about creating internal data structures in C. This course will teach you how to create the following: Linked List Implementation Double Linked List Implementation Array List Implementation Queue Implementation Stack Implementation Binary Tree Implementation All of the implementations described above will be created on video from scratch! You will learn how all of these work internally and when they should be used. This course is a "must have" for someone who has learned the fundamentals of the C Programming Language Who this course is for: C programmers who want to learn how to develop data structures in their applications Less
Expired
159 used