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intro_deeplearning's Introduction

Introduction to Deep Learning

Features:

  1. Vetorised implementation - Number of layers and number of neurons in a layer are user adjustable
  2. Optimizers:
    1. Vanilla gradient descent
    2. Gradient descent with momentum
    3. Gradient descent with Adam
  3. Cost functions:
    1. L2
    2. Cross-Entropy
  4. Activations:
    1. Linear
    2. Sigmoid
    3. Relu
    4. Tanh
    5. Weight Initalizers:
    1. Xavier
    2. He

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