Deep Learning: Recurrent Neural Networks in Python- Udemy

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In this course you will learn all about Hidden Markov Models & Recurrent Neural Networks. First you will be introduced to simple recurrent unit known as Elman-unit then going forward you will be introduced to feedforward neural networks and one of the popular application known as language modeling. Along with these learning sequences you will learn the most common techniques known as Word2Vec, long short-term memory unit (LSTM) and Gated recurrent unit(GRU),

  • Introduction and Outline
  • The Simple Recurrent Unit
  • Recurrent Neural Networks for NLP
  • Advanced RNN Units
  • Appendix

Duration: 4 Hours

Mode: Online Instructor-Led

Fees: $ 120 (Please check website for discount)

Pre-requisites of this course is

  • Calculus
  • Linear algebra
  • Python, Numpy, Matplotlib
  • Write a neural network in Theano
  • Understand backpropagation
  • Probability (conditional and joint distributions)
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