Building ML Regression Models using Scikit-Learn


Building ML Regression Models using Scikit-Learn

This course walks through building Machine Learning Regression Models using Scikit-Learn library from Python.

updated on icon Updated on Sep, 2023

language icon Language - English


architecture icon Machine Learning,Data Science


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Course Description

This course is aimed at students and practitioners of Data Sciences for building Predictive Analytics models for research and commercial purposes.

Machine Learning can be used to solve prediction problems for classification and regression. In this course, we discuss about using Machine Learning for building Regression Models. We will use Python Language.

In Python, we have many options for building Machine Learning solutions like Tensor Flow, Keras, etc. In this project, we use Scikit-Learn.

Scikit-Learn provides a comprehensive array of tools for building regression models (Scikit-Learn also has tools for solving classification problems). The concepts learnt in this project can be extended to build Neural Networks and other types of models using tools like Tensor Flow or Keras, etc using Python or any other language like R.

Before diving into building Regression Models using Scikit-Learn, the course discusses the concepts required to understand the process and mechanism for building such models. As it is easy to understand the concepts working them through Excel, and also it can be experienced visually, we start the course through explanation of the associated concepts using Excel.

This course requires the Learners to have prior knowledge of Computer Software programming, knowledge of programming using Python and also some knowledge of Predictive Analytics.


What will you learn in this course:

  • Predictive Analytics
  • Regression
  • Linear Regression
  • Random Forest Algorithm
  • Support Vector Machines (SVM) Algorithm
  • Programming for Regression using Scikit-Learn


What are the prerequisites for this course?

  • Should have knowledge of writing Computer Software Programs
  • Should have knowledge of Python Programming
  • Should have good knowledge of Excel
  • Some knowledge of Predictive Analytics will be helpful
Building ML Regression Models using Scikit-Learn


Check out the detailed breakdown of what’s inside the course

Welcome to the Course
1 Lectures
  • play icon Introduction 03:56 03:56
Linear Regression
2 Lectures
Further concept
3 Lectures
Advanced Algorithms for Regression
2 Lectures
1 Lectures
The Project
1 Lectures
Course Closing
1 Lectures

Instructor Details



Partha started his career in 1989 as a programmer. In his first assignment, he was involved in development of a Cricket Tournament management system as a part of the team from Centre for Development of Telematics (C-DOT) requested by the Prime Minister of India, Mr. Rajiv Gandhi. Since then Partha has developed Tea Garden automation solution, Hospital Management solution, Travel Management solution, Manufacturing Resource Planning (MRP II) solution, Insurance Management solution and Tax automation solution (for Government of Thailand).

Partha got involved in Telecom solution with project from Total Access Communications, Bangkok in 1996. Partha developed the completed solution architecture and designed & developed the complete infrastructure services and primitives on top of which the end-to-end Customer Care and Billing solution was developed between 1996-1998.

Partha has worked for companies including Amdocs, Portal, Siemens and has developed key components of their solutions. For Siemens, Partha developed the complete BSS suite.

Partha worked with Mobily, Saudi Arabia as the Enterprise Architect and has first-hand of experience of work inside a Telecom Operator.

Partha started his own company, Majumdar Consultancy Pvt Ltd, in 2014. He partnered with a Dubai based businessman to open SI Solutions India Pvt Ltd in 2016. In 2019, he joined Tools and Solutions, Saudi Arabia as Director - Professional Services to establish the Professional Services business.

Partha has recently developed a Remote Control, which can be controlled from a Web Site. The Remote Control can in turn control any device. The Remote Control to be controlled needs having Infra-Red sensing capabilities. The Remote Control is controlled through DragonBoard 410C through a Android Program.

Partha has been working on fine tuning the algorithm for a Access Control System through Face Recognition. The program has been developed using Convolutional Neural Network (CNN).

Partha has also developed a software which tries to predict the Stock Market. The solution has been developed using Recurrent Neural Network (RNN). The solution presently predict with an accuracy of 77%.

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