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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 course 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

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Design patterns provide a template for writing qua... Morelity code. Knowing which design pattern to use in which scenario can be challenging but will make you a master Java programmer. In this course you will take a deep dive into creational patterns, which can help you create more flexible, reusable objects. I will be covering the six most popular creational patterns— Builder, Telescoping Constructor, Singleton, Prototype, Factory and Abstract Factory as well as concepts such as multithreading, mutability, inheritance and Java Heap and Stack workings. I will provide example use cases, complete with implementation instructions and tips for avoiding the unique challenges posed by each pattern also explain how do design patterns work inside Java Heap and Stack Memory. By the end of this course, you'll be equipped with the knowledge and skills necessary to implement each design patterns in your Java projects. Learning Objectives: What are creational design patterns? How to avoid complex constructors? Implementing the Builder pattern Implementing the Telescoping pattern Understanding similarity between Builder and Telescoping pattern Best interview answers for Singleton pattern Questions. Also get a practical idea about the advance concepts such as serialization, cloning, multi-threading and reflection Problem and Solution of Multi-threading with the Singleton pattern Implementing the Prototype pattern Best interview answers for Prototype pattern Questions. Implementing simple Factory pattern Implementing Abstract Factory pattern Who this course is for: Java Developer Java Developer curious about design patterns Java Architect Nail your Java Interviews Web Application Developers Industrial experts API Developers Tech Architects Less
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Hello and welcome to our course on how to develop ... Moreand publish a Google Chrome Extension! This web development course was designed for all levels of programmers, and will provide you with practical JavaScript programming experience. In this course we will build two Chrome extensions and cover the following topics: Introduction and Manifest Content Scripts Messaging Different Parts of the Extension Creating Share Popup Icons Building an Image Downloader Interacting with the DOM Uploading to the Google Chrome Web Store Project source code is available on GitHub. All of the videos in this course are downloadable for offline viewing. English subtitles/captions are available within the course. Thank you for taking the time to read this and we hope to see you in the course! Who this course is for: Web developers interested in publishing a Google Chrome Extension. New JavaScript programmers looking for practical projects. Less
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[100% OFF] Python for Beginners - Learn Python Programming in Hindi Free

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[100% OFF] Learn Next.js Free

SO, YOU’RE LOOKING FOR A COURSE THAT WILL TEACH ... MoreYOU NEXT.JS QUICKLY & IN A FUN MANNER? I’ve got just the course for you! Welcome, my name is Josh Werner with Learn Tech Plus and I’ve put this course together to help people just like you quickly master Next.js...Whether you’re a beginner or experienced with Next.js! If your goal is to become a master of Next.js, then this course is perfect for you. It will get you started on the right path and give you the knowledge and skills you need to master Next.js... Learning Next.js is Not only for Experienced users, but also everyone else. Because when you have mastered Next.js, you can get around Next.js quickly and increase your productivity! In short, a good understanding of Next.js is tremendously beneficial. Now, in this course, we'll go far beyond that. By the end of it, you'll have gained complete proficiency in Next.js even if you're currently a complete beginner! THAT’S RIGHT...NO PRIOR EXPERIENCE OR KNOWLEDGE IS REQUIRED! You don’t need any previous experience or knowledge to take this course. In fact, all you need is a desire to learn and master Next.js. This is not one of those courses that will throw too much at you at once and cause you to get overwhelmed. This is a course that you’ll not only learn so much from, but also enjoy the journey as you’re learning (which is a very important part of the learning process) The course will take you by the hand and teach you everything you need to know step by step and even put your knowledge to practice immediately by showing you how to setup an account with Next.js and How to use Next.js. On top of this, you will also get my continuous support as well to make sure you’re successful with my course. LEARN NEXT.JS BY DOING! (LEARN NEXT.JS FROM SCRATCH!) We will go step by step and cover Next.js. The goal here is to help you A) Setup a Free Account with Next.js B) Work with Next.js Here’s what we’ll cover in the course: 1. We’ll start from the very beginning and explain what Next.js is, why & how it’s used. 2. Introduce you to Next.js Less
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[100% OFF] The Complete Guide Angular 8 for Java Developers 2020 Free

Angular is a TypeScript-based open-source front-en... Mored web application platform led by the Angular Team at Google and by a community of individuals and corporations to address all of the parts of the developer's workflow while building complex web applications. Angular is a complete rewrite from the same team that built AngularJS. Angular is a framework for building client applications in HTML and either JavaScript or a language like TypeScript that compiles to JavaScript. Angular combines declarative templates, dependency injection, end to end tooling, and integrated best practices to solve development challenges. Angular empowers developers to build applications that live on the web, mobile, or the desktop. This course is for existing Java developers who want to learn the popular Angular framework for developing front-end Web interfaces. In the course we cover all of the main principles of building websites in Angular, including the Typescript Language. This is taught with reference to Java and Java web technology examples, making it a very quick and easy way for Java developers to upgrade their skills to Angular. No prior knowledge of Javascript or Typescript is needed, although some basic HTML is useful. Who this course is for: web developers, .net developers, java developers, python developers Less
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[100% OFF] Python and Flask Full-Stack Web Development for beginners Free

A full stack developer is a web developer or engin... Moreeer who can develop both the front end and back end of a website or application. They can tackle projects that involve databases, building user-facing websites, or even work with clients during the planning phase of projects. Full stack web developers usually have some of the following front end and back end skill sets. Front End Skills ( This is used to build the client software or application) HTML CSS Bootstrap JavaScript JSON XML JQuery Angular React Back End Skills ( This is used to build the server software or application) Nodejs Expressjs REST SQL MongoDB Python Java C# ASP PHP RUBY C++ Python is a programming language. Python can be used on a server to create web applications. Flask is a Python framework for building lightweight and dynamic web applications. It helps speed up tedious behind-the-scenes development work, such as URL mapping, and offers more control to the developer to build applications Being a full-stack web developer equips you with the skill set to develop web based projects. You can prototype quickly and switch between front and back end development based on requirements. Projects we will create: Calculator Countdown timer Interactive Quiz Todo List Application URL Shortner Application Basic API Who this course is for: Beginners to Web Development Beginners to Python Beginners to Flask 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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INVOICEZILLA PRO (100% DISCOUNT) (WINDOWS ORIGINAL)

YOUR DOWNLOAD Your download will start automatica... Morelly, or you can manually download from the link below. Download: SharewareOnSale_Giveaway_InvoiceZilla_PRO_hub.exe DIRECTIONS The download link for InvoiceZilla PRO is provided to you above. Your license key for InvoiceZilla PRO is also given above. Download and install InvoiceZilla PRO. After install, run InvoiceZilla PRO and register it with your license key. You can register it by going to ACTIVATION from within the main program window. Enjoy! Be sure to leave a nice comment if you like this offer or ask for help if you have any trouble. Less
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[100% OFF] JavaScript, Bootstrap, & PHP - Certification for Beginners

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[100% OFF] Raspberry Pi meets Arduino Free

This is an advanced level course on Arduino. This ... Morecourse is designed for advanced makers. We’ll help you to get started with the basics of creating circuits with the Arduino and Arduino Mega prototyping board. We will show how a Raspberry Pi and Arduino can communicate with each other. By the end of this course, you would have built Security Systems and Access Control with Arduino using Keypad 4x4 and an Employee entry system using Arduino and RFID sensor. The prerequisite for this course is a basic understanding of electrical and electronic concepts and ability to download and install software on your computer. Along the way, you will learn about programming, sensors, and communications. The course split into three parts: Project 1: In this project, we will teach you how to communicate a message from the Arduino to the Raspberry Pi and vice-versa using a USB serial cable. Project 2: In this project, we teach you how to build an employee entry system using Arduino and RFID sensor module. This project is designed to record the employee details, date and time in PLX-DAQ Spreadsheet to monitor the time and date of entry and exit. Project 3: This is a security related project. We’ll show you how to make a keypad combination lock. In the project, keypad security system and access control with Arduino can change the combination without reprogramming the Arduino. If learning by making sounds like the way to go, then this course is for you! RFID tags are used for everything from credit cards and passports to inventory control and door locks. Everyone should know more than a thing or two about them. With this course, you'll be able to learn how to read, "spoof" and use RFID in both standard and creative ways. Their ubiquitous nature and how little an average citizen knows about them also makes for great science fair and educational projects. To explain RFID, we can use a key and lock analogy. Instead, of the key having a unique pattern, RFID keys hold a series of unique numbers that are read by the lock. It is up to our Arduino sketch to determine what happens when the lock reads the number. The key is the tag, card or another small device we carry around or have in our life. We will be using a passive key, which is an integrated circuit and a small aerial. It uses power from a magnetic field associated with the sensor. If you are a technology enthusiast and want to learn the cutting-edge technology, then this is the right course for you. I will teach you step by step how to go about building this project. I will also share the code with you so that you can replicate the project yourself. At the end of the course, you'll be fully familiarized with Arduino and ready to build your electronic security system. I look forward to you joining this course. It provides the complete source code of the real time project. What are you waiting for? Enroll now! Who this course is for: People who want to try Arduino and learn about microcontrollers Makers who have an existing intermediate or better understanding of electronics Individuals wanting to learn more about RFID applications Create a strict security system by identifying employees and/or clients, or implement anti-theft devices Engineering Students - Electronics, Electrical & Computer Science Electronic Geeks, Hobbiest & Art Students High School Science Students Less
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[100% OFF] The Art of Doing: Master Networks and Network Scanning

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[100% OFF] Deep Learning for Beginners: Neural Networks in R Studio Free

You're looking for a complete Artificial Neural Ne... Moretwork (ANN) course that teaches you everything you need to create a Neural Network model in R, right? You've found the right Neural Networks course! After completing this course you will be able to: Identify the business problem which can be solved using Neural network Models. Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc. Create Neural network models in R using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Neural networks course. If you are a business Analyst or an executive, or a student who wants to learn and apply Deep learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the most advanced concepts of Neural networks and their implementation in R Studio without getting too Mathematical. Why should you choose this course? This course covers all the steps that one should take to create a predictive model using Neural Networks. Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the 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 Deep 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 250,000 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 Practice test, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems. Below are the course contents of this course on ANN: Part 1 - Setting up R studio and R Crash course This part gets you started with R. 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. Part 2 - Theoretical Concepts This part will give you a solid understanding of concepts involved in Neural Networks. In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model. Part 3 - Creating Regression and Classification ANN model in R In this part you will learn how to create ANN models in R Studio. We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. We also solve a regression problem in which we try to predict house prices in a location. We will also cover how to create complex ANN architectures using functional API. Lastly we learn how to save and restore models. We also understand the importance of libraries such as Keras and TensorFlow in this part. Part 4 - Data Preprocessing In this part you will learn what actions you need to take to prepare Data 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. Part 5 - Classic ML technique - Linear Regression 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 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 Neural Network model in R will soar. You'll have a thorough understanding of how to use ANN 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 are some popular FAQs of students who want to start their Deep learning journey- Why use R for Deep Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Deep 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 Neural Network journey Statisticians needing more practical experience Anyone curious to master ANN from Beginner level in short span of time Less
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[100% OFF] 50-point SEO Audit 2020 To Test Your Site Or As Freelancer Free

Learn to do an SEO audit with my comprehensive 50-... Morepoint checklist. You will be able to not only identify problems on your site, but I'll show you how to fix them on your own. My goal is for you to be able to find and fix SEO problems on your site. You will only need to hire freelancers to do the intermediate to advanced technical work that is beyond SEO. Sometimes you will encounter SEO issues that can be fixed by a software engineer or a network engineer. In those cases, I recommend that you hire a freelancer. But in most cases, I show you how to fix the SEO problems on your own. After The Audit, You Will Have: After performing the audit, you'll have a list of improvements and an ability to implement: Making your site mobile Improving site load speed Content quality Optimal content strategy with full site crawling, indexing, and ranking potential Sell SEO Audit Services As A Freelancer Or As An Agency Service SEO audits are a popular service to provide. After this course, you'll be able to impress potential clients that you will give them an impressive and comprehensive site audit with many actionable items they can implement. After that, you will be able to implement most of those action items and make more revenue from that. Who this course is for: Website owners, entrepreneurs, freelancers Less
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[100% OFF] Deep Learning and Neural Networks - Complete BootCamp [2020] Free

Description A complete course on Deep Learning an... Mored Neural Networks concepts in a simplified and easy to understand manner. In this course, you will learn the foundations of deep learning. The course covers following: Introduction to Neural networks and its Applications Basics of Neural Networks NumPy crash Course and Vectorization Shallow Neural Networks Deep Neural networks Key parameters in neural network architecture Let's dive into the course. Less
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[100% OFF] Master MERN Stack by Building Complete Blog Project [2020] Free

Best way to learn new skill is learning by practic... Moree. Welcome to the "Master MERN Stack by Building Complete Blog Project" where we will be building complete blog application using MERN Stack (Node.js, Express, React, Redux and MongoDB). Through the course you will learn how all these different technologies work together. The course is completely a practical hands on project course for building full stack projects using MERN Stack. Because this is a "learn by doing" course, you should be familiar with basics of React, HTML, and CSS. No other knowledge is required. If you successfully complete the course, you will be able to build your own MERN stack application using the best practices tought throughout the course. What will you get at the end of the course? ⦁ You will have Complete Blog App as a portfolio ⦁ You will know implementing CRUD (create, read, update, delete) ⦁ You can covert any HTML&CSS into React application ⦁ You can integrate React with any back-end in an smooth way ⦁ You will know how and where to use React Hooks ⦁ You can use Redux for app state management ⦁ You can create reducers and actions ⦁ You will integrate Redux with React Hooks ⦁ You will know how to debug and test Redux Chrome extension ⦁ You can build an complete backend API with Node.js & Express ⦁ You can deploy to Heroku using Git ⦁ You will know how to test API with Postman What are some app functionalities? ⦁ All Posts ⦁ Featured Posts ⦁ Trending Posts ⦁ Fresh Stories ⦁ Commenting ⦁ Single Post Page ⦁ Posts by Category ⦁ 404 Page The course is for all skill levels and experiences. It does not matter, whether you are developer who is currently learning MERN stack or it is just your first project with these technologies, this course is just for you. All this just for a price of a typical breakfast at restaurant! So, it is the best time to invest into yourself and learn a skill which can boost you career and salary! Who this course is for: Developers who wants to learn how to build and deploy a full stack MERN application Developers who wants to learn React front to Back Developers who wants to build API with Node JS & MongoDB Less
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[100% OFF] Complete MySQL Course: Beginner to Advanced

Complete MySQL course. Learn MySQL from scratch an... Mored go from beginner to advanced in MySQL. 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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223 used

[100% OFF] CSS Flexbox Quick introduction to using FlexBox CSS style Free

Explore more about using Flexbox with examples and... More sample code to get you coding. Flexbox is a one-dimensional layout method for laying out items in rows or columns. Items flex to fill additional space and shrink to fit into smaller spaces Please note that the scope of this course using CSS Flexbox. If you are looking for a more detailed CSS course this course is not for you. Simple course with limited scope designed to be topic specific. Taught by an instructor with over 20 years of Web Development experience. If you've been looking to get started with CSS Flexbox - THIS COURSE IS FOR YOU!!!! Nothing to lose - Fast friendly support is always available to help if you need it. Please note that the SCOPE OF THIS COURSE IS Creating and using CSS flexbox and will not cover complex commands and everything about CSS, HOW TO GET STARTED COURSE - if you are looking at more detailed node or JavaScript content this is not for you. Who this course is for: Web developers Web designers Anyone who is building a website Webmasters and web coders creating web content Less
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74 used, 100% success rate

[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