Arrykrishna Mootoovaloo

Machine Learning Resources

Curated courses and lectures on machine learning and deep learning.

1 min read Machine Learning and Statistics

Below is a curated list of courses, lecture series and schools that I regularly use as references for learning machine learning techniques. Deep learning itself spans several branches, such as natural language processing and meta-learning; resources for these are listed separately.

General Machine Learning

  1. The AI Epiphany (Videos)
  2. ML Tech Talks (Videos)
  3. CPSC 540: Machine Learning 2013 (Lecture Notes, Videos) by Prof. Nando de Freitas
  4. Machine Learning Summer School 2013 (Lecture Notes, Videos)

Deep Learning

  1. Deep Learning with PyTorch (Lecture Notes, Videos) by Prof. Yann LeCun and Alfredo Canziani
  2. MIT 6. S191 Introduction to Deep Learning (Lecture Notes, Videos)
  3. Deep Learning (Lecture Notes, Videos) by Prof. Nando de Freitas
  4. DeepMind x UCL 2020 (Lectures and Videos)
  5. EE-559 – Deep Learning 2019 (Lecture Notes and Videos) by Prof. François Fleuret

Reinforcement Learning

  1. 2021 DeepMind x UCL Reinforcement Learning Lecture Series (Videos, Slides below YouTube Video)

Meta Learning

  1. CS 330: Deep Multi-Task and Meta Learning 2020 (Lectures, Videos) by Prof. Chelsea Finn

Causal Inference

  1. Introduction to Causal Inference 2020 (Lectures and Videos) by Brady Neal
  2. Causal inference meets probabilistic models (Videos)

Gaussian Processes

  1. Gaussian Process and Uncertainty Quantification Summer School, 2020 (Lectures, Videos)

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