Deep Learning (from basics)

 

Table of Contents

Requirements

  • Python language

Description

Following topics are covered as part of the course

  • Explore building blocks of neural networks
    • Data representation, Tensor, Back propagation
  • Keras
    • Dataset, Applying Keras to cases studies, over fitting / under fitting
  • Artificial Neural Networks (ANN)
    • Activation functions
    • Loss functions
    • Gradient Descent
    • Optimizer
  • Image Processing
    • Convnets (CNN), hands-on with CNN
  • Text and Sequences
    • Text data, Language Processing
    • Recurrent Neural Network (RNN)
    • LSTM
    • Bidirectional RNN
  • Gradients and Back Propagation – Mathematics

Who this course is for:

  • Beginner Python developers, Data Science students, Students who have some exposure to Machine Learning
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