Introduce yourself here

Part 1 (2020)
251

@akashpalrecha sure, see right here: :wink:

Basic schedule, we’re on week 5 right now of vision:

Vision

  • Lesson 1: PETs and Custom Datasets (a warm introduction to the DataBlock API)
  • Lesson 2: Image Classification Models from Scratch, Stochastic Gradient Descent, Deployment, Exploring the Documentation and Source Code
  • Lesson 3: Multi-Label Classification, Dealing with Unknown Labels, and K-Fold Validation
  • Lesson 4: Image Segmentation, State-of-the-Art in Computer Vision, Custom Pytorch Models and EfficentNet implementation
  • Lesson 5: Style Transfer, nbdev , and Deployment
  • Lesson 6: Keypoint Regression and Object Detection
  • Lesson 7: Pose Detection and Image Generation
  • Lesson 8: Audio

Tabular:

  • Lesson 1: Pandas Workshop and Tabular Classification
  • Lesson 2: Feature Engineering and Tabular Regression
  • Lesson 3: Permutation Importance, Bayesian Optimization, Cross-Validation, and Labeled Test Sets
  • Lesson 4: NODE, TabNet, DeepGBM (unsure on this, as I haven’t seen NODE be worth it, definitely doing TabNet though)

NLP:

  • Lesson 1: Introduction to NLP and the LSTM
  • Lesson 2: Full Sentiment Classification, Tokenizers, and Ensembling
  • Lesson 3: Other State-of-the-Art NLP Models
  • Lesson 4: Multi-Lingual Data, DeViSe
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