/fastai-lesson-audio

Audio only (MP3) version of fastai lectures (Part 1 2019, Part 2 2018, Intro to ML)

fastai-lesson-audio

Audio only (MP3) version of fastai lectures (Part 1 2019, Part 2 2018, Intro to ML)

Part 1 2019:

  1. Image Classification (1:40:10 - 138MB)
  2. Data Cleaning, Production, and SGD from scratch (1:58:46 - 163MB)
  3. DataBlocks, Multi-label Classification, Segmentation (2:04:54 - 172MB)
  4. NLP, Tabular, Collaborative Filtering, Embeddings (1:43:37 - 142MB)
  5. Backpropagation, Accelerated SGD, Neural nets from scratch (2:13:32 - 183MB)
  6. Regulatization, Convolutions, Data Ethics (2:17:41 - 189MB)
  7. Resnets from scratch, U-nets, Generative Adversarial Networks(GANs) (2:12:05 - 181MB)

Part 2 2018: NOTE: These are the 2018 part 2 lectures, not the recently released 2019 part 2.

  1. Single Object Detection (2:01:13 166MB)
  2. Multi Object Detection (2:05:33 172MB)
  3. NLP Classification and Translation (2:07:54 176MB)
  4. Neural Translation (2:15:56 187MB)
  5. Generative Adversarial Networks(GANs) (2:17:53 189MB)
  6. Image Enhancement (2:15:26 186MB)
  7. Neural Translation (2:02:48 169MB)

Intro to Machine Learning

  1. Introduction to Random Forests (1:17:39 107MB)
  2. Random Forest Deep Dive (1:34:49 130MB)
  3. Performance, Validation, and Model Interprtation (1:23:41 115MB)
  4. Feature Interpretation, Tree Interpreter (1:40:03 137MB)
  5. Extrapolation and RF from Scratch (1:38:31 135MB)
  6. Data Products and Live Coding (1:41:42 140MB)
  7. RF From Scratch and Gradient Descent (1:28:05 121MB)
  8. Gradient Descent and Logistic Regression (1:33:45 129MB)
  9. Regularization, Learning Rates and NLP (1:29:47 123MB)
  10. More NLP and Columnar Data (1:39:15 136MB)
  11. Embeddings (1:36:05 132MB)
  12. Complete Rossman, Ethical Issues (1:41:40 140MB)