Skip to content

Latest commit

 

History

History
207 lines (177 loc) · 15.2 KB

README.md

File metadata and controls

207 lines (177 loc) · 15.2 KB

RoadMap

Current Author: Snehal Saurabh

IMPORTANT NOTE: This roadmap closely follows the roadmap provided by 'RoadMap.sh' with some modifications to it to make it more suitable for beginners based on personal experience. I have also added some additional resources and topics to it.

The steps to be followed are mentioned below:

Mathematical Foundation

  1. Linear Algebra

    Personal Recommendation: - Lectures of Gilbert Strang

  2. Calculus

    Personal Recommendation: - Lectures of Mohit Tyagi (for foundations) if you want an Indian touch.

  3. Probability and Statistics

    Personal Recommendation:
    Foreign:

  4. Optimization

    Personal Recommendation: - Lectures of Stephen Boyd

  5. Information Theory

    Personal Recommendation: - Lectures of David MacKay

Classical Machine Learning

  1. Python Programming

    Personal Recommendation: - Python Tutorials by Corey Schafer

  2. Data Analysis and Visualization

    Personal Recommendation:

  3. Machine Learning

    Personal Recommendation:
    Foreign:

Advanced Machine Learning

  1. Deep Learning

    Personal Recommendation:
    Foreign:

  2. Natural Language Processing

    Personal Recommendation:
    Foreign:

  3. Computer Vision

    Personal Recommendation:
    Theory:

  4. Reinforcement Learning

    Personal Recommendation:
    Theory:

Additional Resources

Additional resources to be added soon.