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Tensorflow 2.0 | Recurrent Neural Networks, LSTMs, GRUs
Rating: 4.1 out of 5(487 ratings)
29,770 students

Tensorflow 2.0 | Recurrent Neural Networks, LSTMs, GRUs

Sequence prediction course that covers topics such as: RNN, LSTM, GRU, NLP, Seq2Seq, Attention, Time series prediction
Created byJad Slim, Amer Sh
Last updated 2/2020
English

What you'll learn

  • RNN
  • LSTM
  • GRU
  • NLP
  • Seq2Seq
  • Attention
  • Time series

Course content

3 sections16 lectures1h 14m total length
  • Introduction - Please watch1:05

    Explore advanced recurrent neural networks, including LSTMs and GRUs, with TensorFlow 2.0, requiring Python and familiarity with TensorFlow or Keras, plus feedforward networks and backpropagation.

  • Additional FREE Content0:05
  • Information on the Full Course0:03

Requirements

  • Python
  • Numpy
  • Tensorflow or keras
  • Feed Forward Neural Networks
  • Back Propagation

Description

This is a preview to the exciting Recurrent Neural Networks course that will be going live soon. Recurrent Networks are an exciting type of neural network that deal with data that come in the form of a sequence. Sequences are all around us such as sentences, music, videos, and stock market graphs. And dealing with them requires some type of memory element to remember the history of the sequences, this is where Recurrent Neural networks come in.


We will be covering topics such as RNNs, LSTMs, GRUs, NLP, Seq2Seq, attention networks and much much more.


You will also be building projects, such as a Time series Prediction, music generator, language translation, image captioning, spam detection, action recognition and much more.


Building these projects will impress even the most senior machine learning developers; and will prepare you to start tackling your own deep learning projects with real datasets to show off to your colleagues or even potential employers.


Sequential Networks are very exciting to work with and allow for the creation of very intelligent applications. If you’re interested in taking your machine learning skills to the next level, then this course is for you!

Who this course is for:

  • machine learning developers
  • Data Scientiests