Machine Learning Resources

Complete roadmap for machine learning and AI, from mathematical foundations to advanced deep learning concepts and practical applications.

Prerequisites

Programming Languages:Python, C++, R, Julia

Frameworks:PyTorch, TensorFlow, Caffe

Libraries:Pandas, Matplotlib, scikit-learn, OpenCV

Mathematical Foundations

Probability and Statistics
MIT OCW: Linear Algebra
Beautiful Linear Algebra Visualization by 3Blue1Brown(Essence of Linear Algebra)

Essential Tools & References

Python
Jupyter Notebook
Sklearn Documentation(Tutorial in itself)
Machine Learning by sentdex (YouTube)(Better than most Udemy courses)

Learning Resources

Search for any AI/ML topic on Medium
Towards Data Science
Making Computers Smart
Machine Learning Mastery
Book on Deep Learning

Machine Learning Courses

Practice Platforms & Computing Resources

Tip: If your machine is not powerful enough, use cloud platforms with free GPU/TPU access

Google Colab(Free GPU, TPU, storage)
Kaggle Notebooks(GPU, TPU, preinstalled dependencies)
Practice ML/DL using Datasets on Kaggle
Access to IIITV's "Param Shavak" supercomputer with GPU accelerators (read specs for details)