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fast-ai

Tags: #course #machine-learning #programming

  • ==Deep learning is a computer technique to extract and transform data by using multiple layers of neural networks==
  • What I’ll learn in this class
    • How to train models that achieve state-of-the-art results in computer vision, natural language processing, tabular data, and collaborative filtering
    • How to turn and deploy models into web applications
    • Why and how deep learning models work
    • Latest deep learning techniques that really matter in practice
    • Implement stochastic gradient descent and a complete training loop from scratch
    • Techniques
      • random forests and gradient boosting [[future]]
      • affine functions and nonlinearities [[future]]
      • parameters and activation [[future]]
      • random initialization and transfer learning [[future]]
      • SGD, momentum, Adam, and other optimizer [[future]]
      • convolutions [[future]]
      • batch normalization [[future]]
      • [ ] dropout [[future]]
      • [ ] data augmentation [[future]]
      • [ ] weight decay [[future]]
      • [ ] image classification and regression [[future]]
      • [ ] entity and word embedding [[future]]
      • [ ] recurrent neural networks (RNNs) [[future]]
      • segmentation [[future]]
  • Tools
  • Lesson 1