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UdemyDeep LearningPaid courseIntermediate level

Tensorflow 2.0 | Recurrent Neural Networks, LSTMs, GRUs (Udemy.com)

Sequence prediction course that covers topics such as: RNN, LSTM, GRU, NLP, Seq2Seq, Attention, Time series prediction

Created by: Jad Slim

Last updated February 2020

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What you will learn

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

How it compares

Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:

  • Rating4.1 out of 5higher than 3% of them
  • Reviews487#70 of 127 by number of reviews
  • Length1.2 hoursshorter than 99% of them
  • Last updatedFebruary 2020earlier than 92% of them

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Course 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!

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Instructor Details

Jad Slim

Jad studied mechanical engineering at the University of Ottawa. Jad also has extensive experience in software development, cloud development, machine learning, computer vision, mathematical modeling, computer simulation, and intelligent systems. Jad has also developed many deep learning applications, and is currently pursuing an interest in autonomous machines and Full Stack Development.

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Reviews

4.1

487 ratings on Udemy

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By Antonio Manuel Sánchez Alonso on 2/17/2025

Pensaba que un curso completo o al menos un poco mas extenso y es mera propaganda de sus cursos

By Ibrahim Gomaa Ibrahim Abdulsalam on 12/2/2024

Good and amazing explanation for RNN and Numpy

By Carlos Rodriguez on 9/23/2021

Esperaba más información para un nivel intermedio, pero para un nivel pre-ingtermedio está bien. AAA

By Musaab Mohammed Ali on 8/27/2020

Not bad to go through it for someone who is just getting started with python and numpy in general. Informative overall.

By Javier Arellano Verdejo on 7/17/2020

Una curso demasiado básico pero supongo será útil para la gente que no sabe nada del tema.

By JosonHui on 7/11/2020

I took a few courses before, all of them explain back propagation not clearly. This course explains clearly !!

By Justin Hemp on 5/22/2020

This was more than I expected from a FREE, 1 hour course (actually only about half an hour of RNN material) !

By Dr. MANOJ KUMAR SHARMA on 4/30/2020

The instructor made easy to understand the concept.

By Kyongmook Lim on 3/30/2020

good stuffs to understand the concept of RNN

By Athul Kumar U on 2/29/2020

It tells only about RNN(which is explained properly) but nothing on LSTMs, GRU thats mentioned in the course heading.

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Quality Score

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Overall Score : 82 / 100