Overview of Machine Learning

According to Forbes, Machine Learning is the most productive analytics skill and therefore multiple industries are moving towards Machine Learning in their business operations. Forbes also says that LinkedIn’s fastest-growing job opportunities belong to Machine Learning and Data Science. Currently, there are over 1,829 job postings open on LinkedIn. As per Glassdoor, Machine Learning professionals easily earn $114,000 base pay per annum.

Watch this complete Machine Learning Tutorial Video

This Machine Learning Tutorial is an introduction to ML to help you learn machine learning so that it gives you knowledge on basics of AI, Machine Learning, ML classes, Neural network basicsActivation function & Multilayer Neuron, Deep Learning with TensorFlow and Optimization functions.
Here we have the list of topics if you want to jump right into a specific one:

What is Machine Learning?

Machine learning is a subset of AI that enables the ability of a machine to perform at ease, where it can learn and develop from the past without being constantly trained. It is mainly used to develop computer programs that get data by itself and use it for learning purpose.

This Machine Learning tutorial will help you master Machine Learning by taking you through a step-by-step approach, so you learn machine learning and Deep learning concepts the right way.

If you have any doubts or queries related to Data Science, do post on Machine Learning Community..

Why is Machine Learning so popular?

Machine Learning is so popular because:

  • Present-day challenges are “high-dimensional” in nature
  • We presently have rich information sources to construct models that take care of issues in high-dimensional space
  • These models can be coordinated into working programming to help the sorts of items currently being requested by industry.

Audience of this Tutorial

This tutorial has been prepared for the beginners as well as for the professionals to help them in understanding from basic to advanced concepts related to Machine Learning. This Machine Learning tutorial will help you in understanding about Machine Learning with Python programming language, from where you will be able to take yourself to a higher level of expertise.

Prerequisites for Machine Learning

Before going through this Machine learning tutorial, you should have a fundamental knowledge of information technologies and understanding of Python programming language. Having prior knowledge of different Python libraries such as NumPy, Pandas, Matplotlib, Scikit-learn will help you in understanding the Machine Learning case studies in a better way so you can move faster on the learning track.

This Machine Learning tutorial covers Introduction of Machine learning, supervised and unsupervised learning, regression and classification, linear and logistic regression techniques, decision tree, k-means clustering and many more. This means you will learn machine learning fundamentals in the best possible manner.

Table of Contents


Artificial Intelligence :

In the today’s world, there is lot of buzz about artificial intelligence. Do you want to know what exactly it is? So let’s begin! Have you ever thought from where we get the recommendation on Facebook or how does on our way google maps recommends us a faster and alternative route and save our time from heavy Read More

Types of Machine Learning – Supervised and Unsupervised Learning

What Are the Different Types of Machine Learning Algorithms?

There are different ways of how a machine learns. In some cases, we train them and, in some other cases, machines learn by their own. Well, primarily, there are two types of machine learning – Supervised Learning and Unsupervised Learning. In this module, we are going to discuss the types of Read More

Datasets for Machine learning

How Do We Get the Right Dataset for Machine Learning?

Data is the most important component of Machine Learning. In order to train models, we should have the ‘right data’ in the ‘right format.’ Now, you must be thinking how do we get the right data, right? Well, getting the right data means collecting or identifying the data that correlates Read More

Data Preprocessing for Machine Learning

Preprocessing Data

Preprocessing Data Data preprocessing is a way of converting data from the raw form to a much more usable or desired form, i.e., making data more meaningful by rescaling, standardizing, binarizing, one hot encoding, and label encoding. The process of getting raw data ready for a Machine Learning algorithm can be summarized in the below steps: Here’s the list of Read More

Machine Learning Algorithms

Understanding Machine Learning

The term ‘Machine Learning’ seems to be a hot cake these days. So, what exactly is it? Well, simply put, Machine Learning is the sub-field of Artificial Intelligence, where we teach a machine how to learn, with the help of input data. Watch this video on Machine Learning by Intellipaat: [videothumb class="col-md-12" id="4gqZLajDWh8" alt="Machine Learning Training for Read More

Classification in Machine Learning

Classification in Machine Learning

Supervised learning techniques can be broadly divided into regression and classification algorithms. In this session, we will be focusing on classification in Machine Learning. We’ll go through the below example to understand classification in a better way. Let’s say, you live in a gated housing society and your society has separate dustbins for different types of Read More

Building Support Vector Machine – SVM Algorithm Models Using Python and Sklearn

What is Support Vector Machine? SVM Algorithm in Machine Learning

Support Vector Machine or SVM algorithm is a simple yet powerful Supervised Machine Learning algorithm that can be used for building both regression and classification models. SVM algorithm can perform really well with both linearly separable and non-linearly separable datasets. Even with a limited amount of data, the support vector Read More

Introduction to Deep Learning

Overview of Deep Learning

From the moment we open our eyes in the morning our brain starts collecting data from different sources. To keep up with the pervasive growth of data from different sources mankind was introduced with modern Data Driven Technologies like Artificial Intelligence, Machine Learning, Deep Learning etc. These technologies have engineered our society in many aspects already Read More

Neural Network Tutorial


Have you ever wondered, how your brain recognizes numbers? No matter how the digits or numbers looks like, brain will relate that to the best possible pattern and concludes the result. This is where the thinking came out to make a something which can recognize similar number patterns, and that is where Neural Networks starts. Watch this Neural Network Read More

TensorFlow and its Installation on Windows

TensorFlow - The Machine Learning Library

Machine learning is eating the software industry and Deep learning is eating machine learning. Google developed this open source software library for the implementation of Machine Learning and Deep Neural Network research. Big IT firms like Facebook, Microsoft, and Google are already implementing and targeting to excel in Deep Learning. Watch this Introduction to TensorFlow Read More

Activation function and Multilayer Neuron

Activation Function :

The activation function of the node defines the output of the node. There are 4 most popular activation function: Step function - It restricts the value of output to 0 and 1. Rectified linear unit - ReLU is like half of step function, it suppresses the negative values. It is the most popular and utilized function. Sigmoid Read More

Neural Networks Basics


In human brain, there are millions and billions of neurons, which keeps learning, updating all the time. The dendrites pass the information from other neuron to the cell, that signal passes through axon reaches the terminal bulb or to other neurons. Dendrites are connected to other neurons. This is called neural networks. Watch this Introduction to Neural Networks video Read More

Deep Learning with TensorFlow-Use Case

Tensorflow- Use Case

Image Recognition and Image classification is one of the most basic yet very popular applications of Deep Learning. But how do we implement the algorithm of Deep Learning in our real-world problems? We certainly need a platform for that. That is when TensorFlow comes into the picture. With the help of this open source Deep Learning Platform Read More

MLlIB Cheat Sheet


It is a Machine Learning library which includes learning algorithms and utilities which helps the programmers to easily practice and use Machine Learning. To work with Machine Learning, one must know the basic concepts and the algorithms required to start with it. This cheat sheet will guide you with all the basic concepts and libraries of Machine Learning you Read More