This repository is a comprehensive, curated collection of links to resources for learning and advancing in data science. It targets aspiring and practicing data scientists, researchers, and engineers by providing a centralized hub for tutorials, books, articles, tools, and datasets across various data science domains.

How It Works

The repository functions as a meticulously organized directory of external links, categorized by topic. It covers a wide spectrum of data science subjects, including AI, cloud computing (AWS), Git, machine learning, statistics, visualization, neural networks, NLP, reinforcement learning, optimization, and programming languages like Python and R. The curation aims to provide high-quality, accessible learning materials.

Quick Start & Requirements

This repository is a collection of links, not executable code. No installation is required. Accessing the resources involves clicking on the provided URLs.

Highlighted Details

• Extensive coverage of AI and Machine Learning concepts, from foundational theory to advanced topics like neural networks and reinforcement learning.
• Detailed sections on essential tools and libraries such as Python (NumPy, Pandas, Scikit-learn), R, SQL, Spark, and Docker.
• Links to numerous free books, online courses (MOOCs), tutorials, and cheat sheets for self-paced learning.
• Curated lists of datasets and resources for practical application and project development.

Maintenance & Community

The repository appears to be a personal collection maintained by Tirthajyoti Sarkar, with links to their LinkedIn and Medium profiles for connection and further content. There is no explicit mention of a community forum or active development team.

Licensing & Compatibility

As a collection of links to external resources, the repository itself does not have a specific software license. The licensing of the linked content varies by the original source.

Limitations & Caveats

The primary limitation is that this is a static collection of links; it does not provide direct access to code or interactive environments. The quality and availability of linked resources depend on the external websites, which may change or become outdated.