Building ML Regression Models using Scikit-Learn

By PARTHA MAJUMDAR, Director - Professional Services

Language: English

This course is for you

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.

Course overview - 10

  • Introduction

  • Understanding Linear Regression

  • Understanding Linear Regression through Excel

  • How to measure goodness of a Regression Model?

  • Scaling Variables

  • Understanding Random Forest Algorithm for Regression

  • Understanding Support Vector Machine (SVM) for Regression

  • Libraries & Functions in Scikit-Learn required for creating Regression Models

  • Building Regression Models using Scikit-Learn

  • Next Steps

Meet your instructor

PARTHA MAJUMDARDirector - Professional Services
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 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 been working on fine tuning the algorithm for an 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%. 

Course by this author

Learn more