Development Data Science Deep Learning

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
Rating: 4.3 out of 5 (324 ratings)
23,667 students
Created by Jad Slim, Rayan Slim
English
English [Auto]
RNN
LSTM
GRU
NLP
Seq2Seq
Attention
Time series

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

Course content

3 sections • 16 lectures • 1h 14m total length

  • Introduction - Please watch
    01:05
  • Additional FREE Content
    00:05
  • Information on the Full Course
    00:03

Instructors

Jad Slim
Developer
Jad Slim
  • 4.6 Instructor Rating
  • 13,843 Reviews
  • 126,018 Students
  • 7 Courses

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


Rayan Slim
Developer
Rayan Slim
  • 4.6 Instructor Rating
  • 13,843 Reviews
  • 137,303 Students
  • 7 Courses

Rayan is a full-stack software developer based in Ottawa, Canada.

Rayan has been appointed as an acting tech lead at Canada's IRCC. His main role is to set up infrastructure monitoring tools to extract health metrics from cloud-native applications.

Rayan also takes leadership roles as he guides other developers towards building Spring Boot applications that implement Enterprise Integration Patterns using the Apache Camel framework. His supervision extends to showing developers how to deploy their applications on the Red Hat Openshift platform using the Kubernetes package manager Helm.

Outside of his daily work, Rayan loves to explore new technologies. He is deeply passionate about Artificial Intelligence and Data Visualization.

In Rayan's free time, he loves to teach!