Flask is a micro web framework written in Python. ... MoreIt is micro framework because it does not require dozens of tools and library. you can customize flask as you want with the help of flask and get creative with it.
What will you learn?
You will Learn about Back End Web Developed
Flask Models
Sqlalchemy
Sqllite
Python Advanced
Databases
Flask Login
Login System
Full CRUD functioning db
Why Flask?
Flask Make it easy to use and good for python beginners.
it is best if you want to make project light weight
Why this Course
we will be making 2 different projects and 1 to work as assignment
to do list app
full blogging web app with login
Project: Library Management System
Who this course is for:
Web Developers
Beginners curious for python
Beginners curious for python web development
Beginners curious for python flask
Beginners curious for python web frameworks Less
Learn the essentials you'll need to get started wi... Moreth AngularJS, a popular open-source web application framework maintained by Google. During this two-hour introductory course, your instructor will introduce you to the basics of AngularJS.The course is designed for individuals and web development professionals that need to understand the fundamentals of AngularJS.Learn about data binding, controllers and creating simple apps, along with additional ways to control the data of AngularJS applications with multiple rows of data and scope binding.
Who this course is for:
This course is for people who are new to Angular Less
Learn how to create and manage Kubernetes using on... Moree of the leading managed services on the market.
Azure Kubernetes Service Zero to Hero admin guide is an intermediate course which describes:
Comparison of Managed vs self-managed Kubernetes solutions;
Pros and Cons of Managed Kubernetes services;
AKS Capacity Analysis;
Detailed AKS network architecture;
How to create an AKS cluster using Azure Portal and Azure CLI;
Integrate AKS with Active Directory;
Create Kubernetes users using self-signed certificates;
How AKS creates and manages Azure storage resources;
AKS monitoring and log debugging.
Who this course is for:
Fearless Kubernetes administrators. Less
This course dives deep into IPv4 addressing and IP... Morev4 subnetting. Starting with binary math and ending with difficult IPv4 subnetting problems this course will prepare you for the subnetting questions on the CCNA, MCSA and CompTIA Network+ exams. Full of shortcuts and useful insights you will gain the clearest understanding of IPv4 addressing and IPv4 subnetting you have every had.
This course divides the material up into small increments and then conquers each with multiple examples, practice questions and video explanations. You will never just get stuck on IPv4 subnetting again.
We actively monitor the Q&A forum and will respond to every relevant question with a helpful answer. We are committed to helping every student achieve their learning goals and will listen to all comments and suggestions. Less
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
This comprehensive course will be your guide to le... Morearning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost!
Enroll in the course and become a data scientist today! Less
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
Apache Kafka has become the leading distributed da... Moreta streaming enterprise big data technology. Kafka is used in production by over 33% of the Fortune 500 companies such as Netflix, Airbnb, Uber, Walmart, and LinkedIn.
To learn Kafka easily, step-by-step, you have come to the right place! No prior Kafka knowledge is required.
If you look at the documentation, you can see that Apache Kafka is not easy to learn...
Thanks to my several years of experience in Kafka and Big Data, I wanted to make learning Kafka accessible to everyone.
We'll take a step-by-step approach to learn all the fundamentals of Apache Kafka.
At the end of this course, you'll be productive and you'll know the following:
The Apache Kafka Ecosystem Architecture
The Kafka Core Concepts: Topics, Partitions, Brokers, Replicas, Producers, Consumers, and more!
Launch your own Kafka cluster in no time using native Kafka binaries – Windows / MacOS X / Linux
Learn and Practice using the Kafka Command Line Interface (CLI)
Code Producer and Consumers using the Java API
Real-world project using Twitter as a source of data for a producer and ElasticSearch as a sink for our consumer
Note: The hands-on section is based on Java, which is the native Kafka programming language. But, good news! Your learning in Java will be completely applicable to other programming languages, such as Python, C#, Node.js or Scala, and Big Data frameworks such as Spark, NiFi or Akka.
Who this course is for:
Developers who want to learn the Apache Kafka Fundamentals, start a cluster and write their first application
Architects who want to understand how Apache Kafka fits into their solution architecture
Anyone looking to learn the full theory of how Apache Kafka works as a distributed system Less
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
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
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
This course will help you learn the basics as well... More as advanced levels of concepts and applications in Adobe Illustrator CC 2020. It covers real world applications of:
1. Logo Design
2. Packaging Design & 3D Mock-Up
3. Typography and Color Theory
4. Social Media Posting
Also, the tools of Adobe Illustrator have been thoroughly explained that will help you in creating the designs with much ease.
Salient Features of this Course:
A comprehensive course consisting of 179 video lectures that are organized in a pedagogical sequence.
Detailed explanation of all tools and commands used in the course.
Step-by-step instructions to guide the users through the learning process.
Practice Test
You will get a Certificate of Completion after completing the course. Less
Hi ! i'm a freelancer from India
you might have... More subscribed to online courses earlier which mess up with lot of boring theory explanations,
and this course is completely different.we will learn the amazing framework(django) practically, it just turns your idea into a startup
django is a kind of framework, where we can do the same thing in different ways, so as per my freelancing experience i will choose only one way to do a particular task. so in this course i will be explaining you my best practices that i do instead of explaining all the possible ways .this is the reason i reduced this course from 24 hours to nearly 4 hours removing all unnecessary stuff, this is just to make you learn quicker.
everything is explained in simple English, instead of using Hi-Fi vocabulary and technical terms. so that it will be completely beginner friendly. Less
Would you like to get a job in the field of IT? Do... More you want to become a Linux system administrator but don’t know where to get started? In this course we will begin by covering the very basics of using the Linux operating system, and move on to the advanced system and networking skills necessary to become a Linux administrator! We will cover the following topics in this course:
Linux installation
Command line usage
Development tools including choosing an IDE
GitHub setup
Complete Meteor.js web project
LAMP stack setup and app deployment
User management
Network administration
Enroll now to receive 7.5+ hours of HD video tutorials, lifetime access and a certificate of completion!
This course is fully subtitled in English.
If you are not convinced, here are a few of the glowing reviews this course has received.
"Course starts out with basic commands and works through more advanced commands as it progresses. The course then goes through add on software and applications following demonstrates basic usages of that application. It was easy to follow along on my personal install of Ubuntu by pausing/review the tutorial as needed. I suggest this method than just sitting and watching the course all the way through. This course is much easier than just reading books. Recommend to friends who just started out in Ubuntu."
"Great explanations. Great teacher."
"It's still early in the course but I've learned a lot. Great job so far."
Thank you for taking the time to read this and we hope to see you in the course!
Who this course is for:
Students who want to get started using Linux
Students interested in learning web development
Student who would like to work as a Linux system administrator Less
Have you always wanted to learn programming but di... Moredn't know where to start ? Well now you are at the right place ! I created this python course to help everyone learn all the basics of this programming language. This course is really straight to the point and will give you all the notion about python. Also, the course is not that long so and the way the material is presented is very easy to assimilate. So if python is something that you are interested about, then you will definitely like this course.
Enjoy your learning :) Less
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
You're looking for a complete Linear Regression co... Moreurse that teaches you everything you need to create a Linear Regression model in R, right?
You've found the right Linear Regression course!
After completing this course you will be able to:
· Identify the business problem which can be solved using linear regression technique of Machine Learning.
· Create a linear regression model in R and analyze its result.
· Confidently practice, discuss and understand Machine Learning concepts
A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.
How this course will help you?
If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular technique of machine learning, which is Linear Regression
Why should you choose this course?
This course covers all the steps that one should take while solving a business problem through linear regression.
Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.
What makes us qualified to teach you?
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course
We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones:
This is very good, i love the fact the all explanation given can be understood by a layman - Joshua
Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy
Our Promise
Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Download Practice files, take Quizzes, and complete Assignments
With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.
What is covered in this course?
This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems.
Below are the course contents of this course on Linear Regression:
· Section 1 - Basics of Statistics
This section is divided into five different lectures starting from types of data then types of statistics
then graphical representations to describe the data and then a lecture on measures of center like mean
median and mode and lastly measures of dispersion like range and standard deviation
· Section 2 - R basic
This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R.
· Section 3 - Introduction to Machine Learning
In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model.
· Section 4 - Data Preprocessing
In this section you will learn what actions you need to take a step by step to get the data and then
prepare it for the analysis these steps are very important.
We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bi-variate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation and correlation.
· Section 5 - Regression Model
This section starts with simple linear regression and then covers multiple linear regression.
We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures. We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results, what are other variations to the ordinary least squared method and how do we finally interpret the result to find out the answer to a business problem.
By the end of this course, your confidence in creating a regression model in R will soar. You'll have a thorough understanding of how to use regression modelling to create predictive models and solve business problems.
Go ahead and click the enroll button, and I'll see you in lesson 1!
Cheers
Start-Tech Academy
------------
Below is a list of popular FAQs of students who want to start their Machine learning journey-
What is Machine Learning?
Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
What is the Linear regression technique of Machine learning?
Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value.
Linear regression is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y). More specifically, that y can be calculated from a linear combination of the input variables (x).
When there is a single input variable (x), the method is referred to as simple linear regression.
When there are multiple input variables, the method is known as multiple linear regression.
Why learn Linear regression technique of Machine learning?
There are four reasons to learn Linear regression technique of Machine learning:
1. Linear Regression is the most popular machine learning technique
2. Linear Regression has fairly good prediction accuracy
3. Linear Regression is simple to implement and easy to interpret
4. It gives you a firm base to start learning other advanced techniques of Machine Learning
How much time does it take to learn Linear regression technique of machine learning?
Linear Regression is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn Linear regression starts from the basics and takes you to advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to remember whatever you have learnt. Therefore, we have also provided you with another data set to work on as a separate project of Linear regression.
What are the steps I should follow to be able to build a Machine Learning model?
You can divide your learning process into 4 parts:
Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part.
Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model
Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the R environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in R
Understanding of Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture in R where we actually run each query with you.
Why use R for data Machine Learning?
Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine learning in R
1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing.
2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind.
3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science.
4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R.
5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science.
What is the difference between Data Mining, Machine Learning, and Deep Learning?
Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions.
Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning.
Who this course is for:
People pursuing a career in data science
Working Professionals beginning their Data journey
Statisticians needing more practical experience
Anyone curious to master Linear Regression from beginner to advanced in short span of time Less
