This repository provides a curated roadmap for individuals aspiring to learn Machine Learning, from foundational mathematics and programming to advanced deep learning concepts and practical application. It targets beginners and intermediate learners seeking structured guidance through the vast landscape of ML resources.

How It Works

The roadmap systematically lists essential prerequisites, including mathematics (Linear Algebra, Calculus, Probability & Statistics) and programming fundamentals (Data Structures & Algorithms, Python). It then progresses to core ML and Deep Learning courses, recommended books, and essential libraries/frameworks like NumPy, Pandas, Scikit-Learn, TensorFlow, and PyTorch, emphasizing official documentation as the primary learning resource.

Quick Start & Requirements

• Installation: No direct installation required; it's a curated list of resources.
• Prerequisites: Basic understanding of mathematics (Linear Algebra, Calculus, Probability & Statistics) and programming (Python, Data Structures & Algorithms).
• Resources: Links to MIT, Coursera, Udemy, Khan Academy, fast.ai, YouTube channels, blogs, research papers, and datasets are provided.

Highlighted Details

• Comprehensive coverage from foundational math to advanced deep learning.
• Curated list of highly-regarded courses, books, and official documentation.
• Includes practical aspects like data preprocessing, visualization, and popular frameworks.
• Points to resources for competitions, research papers, and community engagement.

Maintenance & Community

• Maintained by Shanmukha Sainath, an AI Engineer at KLA Corporation.
• Encourages feedback and suggestions.
• Links to various community platforms like Kaggle, Discord servers, and relevant social media/blogs are implied through resource listings.

Licensing & Compatibility

• The repository itself is likely under a permissive license (e.g., MIT, Apache) given its nature as a curated list. Specific resource links may have their own licensing terms.

Limitations & Caveats

• This is a curated list of external resources, not a self-contained learning platform or tool. The quality and availability of linked resources are subject to change.