Skip to content

Resources

Books

  1. Data Science from Scratch
  2. The Hundred Pages Machine Learning Book
  3. Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow
  4. Deep Learning
  5. Deep Learning with Python
  6. AI and Machine Learning for Coders
  7. Deep Learning from Scratch
  8. Dive into Deep Learning
  9. Probabilistic Machine Learning

Courses

  1. Machine Learning
  2. Backpropagation explained | Part 1 - The intuition - YouTube
  3. Deep Learning Specialization
  4. Tensorflow Developer Professional Certification
  5. Tensorflow: Advanced Techniques
  6. Machine Learning in Production
  7. MIT Deep Learning 6.S191
  8. DS-GA 1008 Deep Learning
  9. CS 182: Deep Learning
  10. CS5785 Applied Machine Learning
  11. Deep Learning: CS 182 Spring 2021
  12. NYU Deep Learning SP20
  13. Deep Learning Crash Course 2021
  14. CMU Neural Nets for NLP 2021
  15. Deep Reinforcement Learning: CS 285 Fall 2020 - YouTube
  16. CS 329S: Machine Learning Systems Design
  17. Full Stack Deep Learning
  18. STAT 479: Machine Learning University Wisconsin-Madison
  19. Made With ML
  20. Practical Deep Learning for Coders (fast.ai)
  21. CS 330 Deep Multi-Task and Meta Learning (stanford.edu)

Blog Posts

  1. MIT Deep Learning Basics: Introduction and Overview with TensorFlow | by Lex Fridman | TensorFlow | Medium
  2. Transformers from Scratch (e2eml.school)
  3. E2EML.school
  4. Machine Learning Glossary

Educational Projects

  1. Titanic - Machine Learning from Disaster
  2. House Prices - Advanced Regression Techniques
  3. Heart Disease UCI
  4. Digit Recognizer
  5. Sentiment140 dataset with 1.6 million tweets
  6. Pima Indians Diabetes Database
  7. Breast Cancer Classification
  8. TMDB Box Office Prediction
  9. Mall Customer Segmentation Data
  10. Store Item Demand Forecasting Challenge
  11. Market Basket Optimization
  12. New York City Taxi Trip Duration
  13. SMS Spam Collection Dataset
  14. (MBTI) Myers-Briggs Personality Type Dataset

Tools and Platforms

  1. Weights & Biases – Developer tools for ML (wandb.ai)
  2. MLflow - A platform for the machine learning lifecycle | MLflow
  3. PlotNeuralNet: Latex code for making neural networks diagrams (github.com)

Frameworks

  1. TensorFlow
  2. PyTorch