Teaching Resources

This post contains resources which I believe to be the best at teaching what they do. When I find improved resources I will make sure to replace older resources.

Table of Contents

  1. Videos
  2. Blog Posts
  3. Data Science
  4. Courses or Course Material
  5. Personalities
  6. Summary Material



  • Full course in python programming from beginners to introduction of classes (ref)


  • (6-7) Linear algebra for beginners (ref)

Neural Networks

  • Playlist by 3Blue1Brown on fully connected neural networks (ref)

Deep Learning

  • Tutorial in PyTorch (ref)

Transformer and Attention

  • Brief introduction to transformer models (ref)
  • Step by step explanation of transformers (ref)

Blog Posts

Machine Learning

  • Wonderful blog by OpenAI engineer on NN and ML (ref)

Transformers and Attention

  • A blogpost explaining the transformer: The Illustrated Transformer (ref)
  • The annotated transformer (ref)
  • Transformers are GNN (ref)
  • A blogpost explaing Attention in Machine Translation (ref)
  • The annotated encoder decoder with Bahdanau attention. Similar to the annotated transformer but with the paper introducing attention by Bahdanau (ref)

Courses or Course Material


  • NLP Course (ref) and associated github (ref)

Deep Learning

  • Deep learning (ref)

Machine Learning

  • Course in general ML by fast.ai (ref)



  • (10) 3Blue1Brown by Grant Sanderson (ref)

Machine Learning and statistics

  • StatQuest by Josh Starmer (ref)


Data Vizualization

  • A book on data vizualization (ref)


Machine Learning

  • State-of-the-art (ref)


  • State-of-the-art (ref)
  • Common Crawl (ref)

Resource Collection

Data Science

  • A look up resource for data science concepts (ref)


  • A list of pytorch resources (ref)

Summary Material

  • Spectra Pub, a Machine Learning Review Paper Competition. Full of great review papers of entire fields. (ref)
Kenneth Enevoldsen
Kenneth Enevoldsen
PhD student in Multimodal Representation Learning

My research interests is in multimodal representation learning with application in decision support systems in Psychiatry and in the Covid-19 response.