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

You're looking for a complete Artificial Neural Network (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

[100% OFF] MERN Stack Master Course - Building your own Instagram Free

MERN stands for MongoDB, Express.js, React.js and ... MoreNode.js - and combined, these four technologies allow you to build amazing web applications In this course we will be building FULL FLEDGED INSTAGRAM website and it will be a lots of fun as we building this together. This course covers - Building an backend API with Node.js & Express Testing API using Postman JWT based authentication Image upload Context API for state management React Hooks React Router hooks Protecting routes or endpoints Sending Emails Forgot & Reset Password This course is NOT an introduction course to React & Node js. It is fully hands on course for building full stacks websites using MERN Less
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[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
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[100% OFF] JavaScript, Bootstrap, & PHP - Certification for Beginners

A Comprehensive Guide for Beginners interested in ... Morelearning JavaScript, Bootstrap, & PHP Less
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[100% OFF] Python for Beginners - Learn Python Programming in Hindi Free

Head into the world of Python Programming, easy an... Mored detailed. Build your own applications, right from the basics! Less
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[100% OFF] JavaScript + ES6 + ES7 + ES8 + ES9 -> The Complete Guide Free

Welcome to my new course: 'JavaScript + ES6 + ES7 ... More+ ES8 + ES9 -> The Complete Guide'. This course starts from scratch, you neither need to know any pre-requisite programming knowledge nor any language expertise. From the environment Setup to Development, this course covers almost each and every concept required to become an expert JavaScript developer. Having a deep-dive of the concepts in this course, you'll learn all about: JavaScript: Development Environment Setup Fundamentals Operators Control Flow Arrays Functions Objects Prototypes Patterns To Create Objects Error Handling Miscellaneous Objects Debugging in Chrome Shopping Cart Project: Putting All Together ES6: Features with their Syntax Modules Class Symbols Iterators & Generators Promises Maps & Sets Extensions of Built-in Objects Reflect API Proxy API ES7: New Features ES8: New Features ES9: New Features World Weather Project: Putting All Together Course Roundup and many more... This course will assist: In becoming an proficient 'JavaScript Developer' and Inclining towards the learning/ understanding of any client/ server side programming language. Why JavaScript? JavaScript (JS) is a lightweight, interpreted or JIT compiled programming language with first-class functions. Most well-known as the scripting language for Web pages, many non-browser environments also use it, such as Node.js and Apache CouchDB. JS is a prototype-based, multi-paradigm, dynamic scripting language, supporting object-oriented, imperative, and declarative (e.g. functional programming) styles. The standard for JavaScript is ECMAScript. As of 2012, all modern browsers fully support ECMAScript 5.1. Older browsers support at least ECMAScript 3. On June 17, 2015, ECMA International published the 6th major version of ECMAScript, ECMAScript 2015. Since then, ECMAScript standards are on yearly release cycles. This course covers up to the latest version of JavaScript, which is currently ECMAScript 2019. Why we should learn JavaScript & the reasons are: Open Source Language: Freely Available. Much more than Scripting programming language. Scalability and Performance Features. Evolving steadily & ES6 represents the BEST !!! Much JavaScript-related innovation in the Market. Base of most of the frameworks like Angular. Supported by a broad coalition of companies. Who this course is for: Be a JS Ninja by understanding the most popular programming language in the world viz. JavaScript. Newcomer as well as experienced having the experience with JavaScript (ES5/ ES6) and know the basics of the language. Understanding the new Features and Additions, brought by ES6 (including ES5) to JavaScript. Understand the basics to move head with the popular libraries/frameworks like jQuery, React, Angular or NodeJS. Understand how JavaScript actually works internally. Less
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[100% OFF] Front End Web Development For Beginners (A Practical Guide) Free

Learn Front End Web Development Student reviews... More: "Great Course" -Rich Helton "This is great training for beginners and aspiring front end web developers this is simple yet very very informative" -Leynard Caballero Villagracia "I think it is a great course for the beginning level." -Hoang Cong "Great course and perfect explanation specially for beginners." -Kenan Dedoviq "Easy to understand for beginners..." -Hiren Bechra "Yeah, it's been a good match for me definitely. The content and the way of teaching by the mentors is very effective and efficient. Any one can begin with building web pages, taking up this certain course" -Abhinav Anand ======================================================== Not sure yet? Just scroll down and watch the free preview lectures! Enroll with confidence! Your enrollment is backed by Udemy's 30-day, no-questions-asked, money-back guarantee! What are the requirements? · All information and resources are included in this course. What am I going to get from this course? · Learn how to hand code HTML and CSS · Work with Bootstrap 4 · Build 2 great projects to get you started on your Front End Web Development education What is the target audience? · Anyone who wants to dramatically increase their Front End Web Development Skills! Less
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[100% OFF] Mastering Agile Scrum Workshop Free

UPDATE FOR 2020 with Tanmay's latest knowledge on ... MoreAgile Scrum Certification! This course is about learning the latest Agile Scrum methodology for the Software development field. In this course, you will learn all other Agile methodologies along with detailed information on Scrum. By this course, experienced project managers can grow in their careers and get the next level of opportunity as an Agile Scrum Master and the junior team members can learn the process of the Agile Scrum methodology. The biggest target audience is at any experience level who wants to learn Agile Scrum in detail and apply in the career!!! Who this course is for: Project Managers who would like to be an Agile Scrum Master Qualifying Agile Scrum Master Certification Exam People who want to learn about Agile Scrum Developers, BAs, Architects, Analysts, Designers, Managers, etc Less
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[100% OFF] Home Business Basic Sales & Marketing Tools

Learn About Some Of The Basic Sales & Marketin... Moreg Tools For A Home Business Less
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[100% OFF] Learn to Code with Python 3! Free

If you would like to learn Python 3 programming in... More 2020, you are going to LOVE this course! Get started with the most beginner friendly programming language and start writing your very own programs today! We will cover the following topics in this course: Introduction to Python and setup Python programming basics Functions - coding exercises Lists, tuples and dictionaries Files in Python 3 Error handling Object oriented programming Date & time Regular expressions Interacting with HTTP Networking in Python 3 Threading E-mails, PDFs, images This course was designed for absolute beginners who wish to master the Python programming language. All lectures are downloadable for offline viewing. English subtitles and a certificate of completion are are available as well. Thank you for taking the time to read this and we hope to see you in the course! Who this course is for: Students interested in learning the Python programming language. Students who wish to pursue a career in software development. Less
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[100% OFF] Partnership Accounting Free

Partnership accounting will cover accounting topic... Mores related to a partnership form of business entity. This partnership course will focus on the accounting issues that are different in a partnership as compared to other types of entities like a sole proprietorship or corporations. As we focus on the differences, we always want to keep in mind the similarities in accounting for different business entities. Most of what we have learned about the double entry accounting system and day to day accounting transactions in prior courses will remain the same. We are concentrating on the areas that will different because the differences are where the new information lies. We will start by defining what a partnership is and comparing the characteristics of a partnership with other business entities. Understanding one business entity and its components are often best learned by contrasting them with the attributes of others, always considering the relative pros and cons, thinking of situations and circumstances that would benefit one form of business entity over another. The course will discuss the process for setting up a new partnership, typically starting with the partners contributing capital to the partnership, requiring us to record the contribution and the capital accounts. We will discuss the allocation of net income to the partners, one of the primary differences between a partnership type of entity and other types of entities. There is a lot of flexibility for net income allocation in a partnership, and this is one of its primary benefits. The course will cover the recording of partnership draws, how to record them, as well as the closing process for a partnership. The steps of the closing process will be much the same as those for any business entity except for the allocation of net income to the partners. We will consider the situation where a partner leaves a partnership or where a new partner is added. The transactions related to a partner leaving or being added is unique to a partnership entity. The course will cover a partnership liquidation process or closing process. The liquidation process is a very useful exercise for any entity because it allows us to do take apart a business. We have discussed the process of putting new busses together in prior courses, but to fully understand how something works we must also take it apart. The liquidation process is particularly important for a partnership entity because it emphasizes the capital accounts and the process necessary to reduce the likelihood of problems during the process. We also include a comprehensive problem designed to take a step back and consider all the similarities between business entities so that we can put the differences we have studied in this course into perspective. The comprehensive problem will cover the entire accounting cycle from entering journal entries and posting to the general ledger, to recording adjusting entries and creating the financial statements, to the closing process. The course also includes definition and key accounting terms related to partnerships. In addition to the instructional videos, this course will include downloadable • Downloadable PDF Files • Excel Practice Files • Multiple Choice Practice Questions • Short Calculation Practice Questions • Discussion Questions The PDF files allow us to download reference information we can use offline and as a guide to help us work through the material. Excel practice files will be preformatted so that we can focus on the adjusting process and learning some of the basics of Excel, like addition, subtraction, and cell relationships. Multiple choice example question helps us improve our test-taking skills by reducing the information into the size and format of multiple choice questions and discussing how to approach these questions. Short calculation questions help us reduce problems that have some calculation down to a short format that could be used in multiple choice questions. Discussion Question will provide an opportunity to discuss these topics with the instructor and other students, a process many students find very helpful because it allows us to see the topic from different viewpoints. Who will we be learning from? You will be learning from somebody who has technical experience in accounting concepts and in accounting software like QuickBooks, as well as experience teaching and putting together curriculum. You will be learning from somebody who is a: • CPA – Certified Public Accountant • CGMA – Chartered Global Management Accountant • Master of Science in Taxation • CPS – Certifies Post-Secondary Instructor • Curriculum Development Export As a practicing CPA the instructor has worked with many technical accounting issues and helped work through them and discuss them with clients of all levels. As a CPS and professor, the instructor has taught many accounting classes and worked with many students in the fields of accounting, business, and business applications. The instructor also has a lot of experience designing courses and learning how students learn best and how to help students achieve their objectives. Experience designing technical courses has also benefit in being able to design a course in a logical fashion and deal with problems related to technical topics and the use of software like QuickBooks Pro. Content Includes: • Process for setting up a partnership • The allocation of net income to partners • The recording of partner withdrawals • Recording the partnership closing process • Journal entries related to a partner leaving the partnership • Journal entries related to adding a new partner to the partnership • The liquidation process for a partnership • A comprehensive problem on the accounting cycle • Key terms definitions and explanations related to partnerships Who this course is for: Accounting students Business owner Anyone who whats to learn accounting Less
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[100% OFF ] Learn Java by building 17 projects step by step Free

Learning to code can be both fun and rewarding . J... Moreava is a useful ,robust and popular programming language to embark on that journey. This course is a practical Hands-on course from the first to the last section. The best way to learn is by doing so you will be doing a lot of coding. Java is a case-sensitive, modern, general-purpose, object-oriented programming language. One of the reasons Java is so popular is that it is platform independent . You only need to write java code once and then run it on any platform be it mac, windows or Linux. In this course we will create 17 practical and useful projects step by step. The projects include: Calculator Digital Clock Weight Converter Temperature Converter Height Converter Random Number Generator BMI Calculator Tool Percentage Calculator Word Count Tool Add number program Program to determine Even numbers Program to determine Leap Year Program to calculate area and perimeter of a circle Program to find highest number Program to find Prime Numbers Program to create a triangle Program to determine largest numbers This course will guide you through java basics, its core syntax, and the fundamentals of writing strong java code. I will show you how to install Java JDK and NetBeans IDE. Netbeans is a great IDE for developing in java, and then dive into the language itself. Along the way, we will cover topics such as: Declaring and initializing variables with a variety of data types Exploring Basic Arithmetic operators Troubleshoot Compile errors Controlling flow with conditional code Creating Method Creating Event Handler methods Using Component controls and changing their properties If java is your first step into programming or adding it your existing skillset, these training videos will help you understand the language and use it to build your own great software. Less
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[100% OFF] Machine Learning with Jupyter Notebooks in Amazon AWS Free

Are you a company or a IT administrator, data cent... Moreer architect, consultant, enterprise architect, data protection officer, programmer, data security specialist, or big data analyst and want to gain fundamental and intermediate level skills and enjoy a fascinating high paying career? Or maybe you just want to learn additional tips and techniques taking to a whole new level? Welcome to Machine Learning, Reinforcement Learning and AWS course For Beginners - A one of its kind course! The flipped classroom model with hand-on learning will help you experience direct into the course as your begin your learning journey. Be sure to watch the preview lectures that set course expectations! In this course, you'll learn and practice: Machine Learning topics Jupyter Notebooks Reinforcement Learning Machine Learning Services in AWS AWS Sagemaker Dynamic Programming Q-Learning Understand best practices, and much more.... You will also get complete resources, toolkit, and code where applicable with this course! We've built this course with our Team ClayDesk of industry recognized developers and consultants to bring you the best of everything! So, if you would like to: - start your freelancing career and consult companies, this course is for you - gain marketable skills as an IT expert and professional, this course is for you - This course is not designed for advanced level students ...this Machine Learning, Reinforcement Learning and AWS course is exactly what you need, and more. (You’ll even get a certification of completion) See what our students say “It is such a solid course that covers all important areas of machine learning, and I now know hoe to predict future products based on their features. Simply awesome!.” - Alex Neuman “This is such an awesome course. I loved every bit of it – Wonderful learning experience!” Ankit Goring. Join thousands of other students and share valuable experience Why take this course? As an enterprise architect consulting with global companies, technology evangelist, and brand innovator, I have designed, created, and implemented enterprise level projects, I am excited to share my knowledge and transfer skills to my students. Enroll now in Machine Learning, Reinforcement Learning and AWS today and revolutionize your learning. Stay at the cutting edge of Machine Learning and Data Science —and enjoy bigger, brighter opportunities with AWS. Qasim Shah Who this course is for: Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game Anyone who is curios about machine learning Less
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[100% OFF] Data Visualization in Excel: All Excel Charts and Graphs Free

What are the chart types I will learn in this cour... Morese? Excel offers the following major chart types. All of these are covered in this course Column Chart Line Chart Pie Chart Doughnut Chart Bar Chart Area Chart XY (Scatter) Chart Bubble Chart Stock Chart Surface Chart Radar Chart Combo Chart Pivot Chart Sparklines And many other creative ones :) How are charts useful in Excel? A chart is a tool you can use in Excel to communicate data graphically. Charts allow your audience to see the meaning behind the numbers, and they make showing comparisons and trends much easier. What are the benefits of using charts in Excel? Excel charts allow spreadsheet administrators to create visualizations of data sets. By highlighting a set of data within an Excel spreadsheet and feeding it into the charting tool, users can easily create various types of charts in which the data is displayed in a graphical way. This course will answer all the questions that would pop up while you set to visualize your data using Excel charts such as: How do you make Excel charts look better? How do you format a chart in Excel? What are the different elements of charts? How do I make those awesome infographics that I see in fancy magazines and TV reports? How do I create a comparison chart in Excel? What is the best chart to use for comparison? And many more... How is this course different from other resources available online? Most courses cover only teach how to draw different types of charts in Excel. The main point is missed. The main point of creating a chart is that you want to convey a message or tell a story using the chart. In this course, once you have learnt all the charting tools, you will also learn how you should create a chart. How you can highlight your message and avoid clutter in the chart, so that when your audience looks at the chart, the message is clearly conveyed to them. Who this course is for: Anyone curious to master charts in excel from beginner to advanced in short span of time Less
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[100% Off] Learn SQL for Beginners: The Comprehensive Hands-on Bootcamp Free

Learning databases and database theory can be easy... More if you have the right teacher. This university level course will give you a solid understanding of how databases work and how to use them. In the course, we will be using PostgreSQL which is one of the top two databases most demanded in industry. This course will advance your skills as a developer. This course is very practical and applicable. It focuses on teaching you skills you can use. Presented with high-quality video lectures, this course will visually show you many great things about relational databases and PostgreSQL. This course is taught by two teachers. One of your teachers is a tenured professor in California. Your other teacher is a Professional Developer. Both of these teachers will be on screen, sharing their wisdom and knowledge with you. This is just some of what you will learn in this course: Learn to succeed as a student Master database fundamentals Build a database for tracking movie rentals Understand schema, data hierarchy, and normalization Learn validation, data integrity, and ACID transactions Master using key fields and ensuring referential integrity Learn how to do SQL commands at the terminal and in code editors Solidify concepts with abundant hands on exercises which also have video solutions provided Acquire the ability to read PostgreSQL database documentation Learn how to install PostgreSQL on Windows, Linux, and Mac Master building databases, tables, and relationships between tables Master creating, reading, updating, inserting, and deleting records Gain the ability to do subqueries and aggregate functions Master using grouping, having, limit, fetch, and offset Learn how to use JSON inside SQL using PostgreSQL Master joins to query multiple sets Master filtering records in queries MASTER SQL & PostgreSQL! This is an amazing course! This course will change your life. Being skilled at using relational databases and SQL will serve you and your career well. This course will increase your proficiency, productivity, and power as a programmer. You are going to love this course and it will forever change your life. Your satisfaction is guaranteed with this course. Join us now and enroll! Who this course is for: This is a first semester university level SQL database course. This course is ideal for beginners wanting to learn databases & SQL programming. Less
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[100% OFF] Flutter and Firebase Part 1 (Real-Time Database) free

This class covers Flutter and Firebase Real-time D... Moreatabase in more details. The class focuses on CRUD (Create, Read, Update and Delete) of Firebase Real-time Database. Students will learn how to integrate Firebase into flutter applications. Students will also learn how to create, read, update and delete from real-time database in more details. Aside Firebase and database, students will also learn how to design interfaces in flutter, including how to use pop-ups and dialog box in flutter. Students taking this class should have basic knowledge in programming. Basic knowledge and experience in flutter and/or dart is preferred but not a requirement. Less
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[100% OFF] Python Game Development™: Build 5 Professional Games Free

Have you ever wanted to build a game with a graphi... Morecal interface but didn't know how to? Maybe you even know how to create tools on a command line but have no idea how to convert it into a graphical interface that people can click on. In this course, we will be learning Python GUI Programming + Turtle + other advanced python modules to build graphical user interfaces (GUI) and games from scratch. Game projects covered: 1. Solitaire 2. Space Shooter 3. Chain Reaction 4. Pac-man 5. Car Racing 6. Snake and many more. Basic Python course Highlights: Installing Python Running Python Code Strings Lists Dictionaries Tuples Sets Number Data Types Print Formatting Functions Scope args/ kwargs Built-in Functions Debugging and Error Handling Modules External Modules Object-Oriented Programming Inheritance Polymorphism Encapsulation Advanced Methods Iterators Closures and much more! 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. 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