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Machine Learning Course

Machine Learning Python MIT Size Contributors

Overview

This repository holds the contents of machine learning course. This course helps you to gain the basic and sound knowlege in machine learning domian. It is an one stop to all machine learning concepts where every algorithm is explained with examples, sample codes in jupiter notebook. At the end of the course you will be able to build a real time application in Machine Learning domain.

What is Machine Learning?

Machine learning is the scientific study of algorithms and statistical models that computer systems use in order to perform a specific task effectively without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.

What will I learn from this course?

  • How to apply Supervised and Unsupervised algorithms for different applications.
  • Hands on Experience on Machine learning Algorithms.
  • Developing a real time applications in Machine Learning domain.

Prerequisites

The things that you must have a decent knowledge on:

    1. Python
    2. Linear Algebra
    3. Machine Learning Terminology

Dependendicies

      python 3.6.x

Installation

  • Clone this repository:
      git clone https://github.com/syamkakarla98/Machine_Learning_Course.git

  • Or click here to download this repository: Click Here

  • Goto Machine_Learning_Course folder:

      cd Machine_Learning_Course
  • This project is fully based on python. So, the necessary modules needed for computaion are placed in setup.py:
      pip install -r setup.txt

How to use

  • Go to the directory and use below command to access the jupyter notebooks.
     jupyter notebook

Authors

License

This project is licensed under the MIT License - see the LICENSE.md file for details.