Building ML Regression Models using Scikit-Learn
This course walks through building Machine Learning Regression Models using Scikit-Learn library from Python.
Lectures -12
Resources -4
Duration -2 hours
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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.
Goals
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
Prerequisites
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
Curriculum
Check out the detailed breakdown of what’s inside the course
Welcome to the Course
1 Lectures
- Introduction 03:56 03:56
Linear Regression
2 Lectures
Further concept
3 Lectures
Advanced Algorithms for Regression
2 Lectures
Scikit-Learn
1 Lectures
The Project
1 Lectures
Course Closing
1 Lectures
Instructor Details
PARTHA MAJUMDAR
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