Study Resources

A curated collection of study materials, courses, YouTube playlists, and resources for Data Science, AI, and Machine Learning.

Machine Learning

Machine Learning by Krish Naik

▶ YouTube

Complete machine learning course covering all fundamentals.

Machine Learning by CampusX

▶ YouTube

Hands-on machine learning with Python.

Machine Learning by Andrew Ng

📚 Coursera

The classic ML course by Stanford professor.

Machine Learning by Edureka

▶ YouTube

Practical machine learning tutorials.

Deep Learning

Deep Learning by CampusX

▶ YouTube

Comprehensive deep learning course with PyTorch.

Deep Learning by Krish Naik

▶ YouTube

Neural networks and deep learning fundamentals.

Deep Learning.AI Courses

📚 DeepLearning.AI

Specialization courses by Andrew Ng.

PyTorch Deep Learning

▶ YouTube

Deep learning with PyTorch framework.

Natural Language Processing

NLP by CampusX

▶ YouTube

Natural language processing with transformers.

NLP by Krish Naik

▶ YouTube

Text processing and NLP fundamentals.

NLP with Transformers

▶ YouTube

Modern NLP using transformer models.

Hugging Face Course

🔗 Website

Free NLP course by Hugging Face.

Computer Vision

Computer Vision by CampusX

▶ YouTube

Image recognition and object detection.

Computer Vision by Krish Naik

▶ YouTube

CNN and vision transformers.

OpenCV Python

▶ YouTube

OpenCV for image processing.

Data Science

Statistics & Probability

▶ YouTube

Statistics and probability for data science.

Data Analysis with Python

▶ YouTube

Pandas, NumPy for data analysis.

Data Visualization

▶ YouTube

Matplotlib, Seaborn, Plotly visualization.

Mathematics

Linear Algebra by 3Blue1Brown

▶ YouTube

Visual introduction to linear algebra.

Calculus by 3Blue1Brown

▶ YouTube

Essence of calculus.

Discrete Mathematics

▶ YouTube

Discrete math for computer science.

Statistics & Probability - Khan Academy

🔗 Website

Free statistics course.

Research Papers

  • Attention Is All You NeedTransformer architecture

    Vaswani et al., 2017

  • ResNetDeep residual learning

    He et al., 2015

  • BERTLanguage understanding

    Devlin et al., 2018

  • GPT-3Language models

    Brown et al., 2020