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Deep Learning with Transformers

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

Course Preview Video

  • Categories

    IT & Software Systems

  • Duration

    06:47:12

  • 1 Students Enrolled

Description

Learn the state-of-art Transformers for NLP and how to implement them from scratch!


Basic knowledge
  • Python and a Basic Knowledge about Neural Networks

What will you learn

In this course, we will cover the following in full detail:

  • Course Outline
  • Sequence Modelling
  • RNNs and LSTMs
  • Attention Mechanism
  • How Attention Works
  • Word Embeddings
  • Visualizing and Measuring Word Embeddings
  • Introduction to Transformers
  • Input Embeddings
  • Positional Encoding
  • MultiHead Attention
  • Concat and Linear
  • Residual Learning
  • Layer Normalization
  • Feed Forward
  • Masked MultiHead Attention
  • MultiHead Attention in Decoder
  • Cross Entropy Loss
  • KL Divergence Loss
  • Label Smoothing
  • Dropout
  • Learning Rate Warmup

All concepts discussed above are visualized with diagrams to ease your understanding! 

After that, we will implement all what we've learned above to build a Chatbot in PyTorch!

Course Curriculum
Number of Lectures: 42 Total Duration: 06:47:12
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