Deep Learning: Recurrent Neural Networks in Python Training Course


Deep Learning: Recurrent Neural Networks in Python Certification Training Course Overview

Enroll for Deep Learning: Recurrent Neural Networks in Python training course from Koenig Solutions. Deep Learning: Recurrent Neural Networks in Python training course will help you learning 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.

 

Target Audience:

The course is perfect for professional having knowledge in Python, Numpy, Matplotlib


Deep Learning: Recurrent Neural Networks in Python Training Course (Duration : 8 Hours) Download Course Contents

Live Virtual Classroom (Instructor-Led)

Fee : On Request
9 AM - 5 PM (Flexible Time Slots for 4 hours option)




April
8 Hours/Day
19
19-20
May
8 Hours/Day
03
09
10
17
03-04
09-10
10-11
17-18
June
8 Hours/Day
07
13
14
21
07-08
13-14
14-15
21-22
July
8 Hours/Day
05
11
12
05-06
11-12
12-13
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request

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Course Prerequisites

Knowledge of Python, Numpy, Matplotlib.

 

Learning Objectives

After completing this course, you will learn how to:-

 

  • Apply RNNs to Time Series Forecasting (tackle the ubiquitous "Stock Prediction" problem) Improve forecasting
  • Apply RNNs to Image Classification
  • Write various recurrent networks in Tensor flow 2
  • Understand how to mitigate the vanishing gradient problem