Getting Started with Deep Learning with R [Integrated Course]

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Getting Started with Deep Learning with R [Integrated Course]

Akash Tandon

Learn one of the most in-demand skills – Deep Learning
This title is available to pre-order now and is expected to be published in
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Video Details

ISBN 139781788399029
Course Length3 hours

Video Description

Are you looking at implementing deep learning techniques in your data science projects? If yes, then this course is for you.

Deep learning has become one of the most popular and exciting fields of our time and age. Deep learning gives you unimaginably powerful insights into data.

This course is a blend of text, videos, code examples, quizzes, and a mini project which together makes your learning journey all the more exciting and truly rewarding. This course is meticulously designed and developed in order to empower you with all the right and relevant information on deep learning.

Let’s take a look at this learning journey. The course begins with an introduction to deep learning. You will then learn how to implement various neural networks such as convolutional neural network with R. Moving ahead, you will explore the advanced topics: H20 and MXNet. Finally, the course includes a case study that covers the MNIST image dataset.

By the end of this course, you will have a strong knowledge of deep learning techniques and will be able to implement in your real-world datasets.

Key Features

  • Implement various neural networks with the help of real-world examples
  • Gain mastery over the concepts you will learn by testing yourself with challenging assessments
  • All the advanced techniques and concepts through a case study

Who this course is for

The course is intended for data science professionals who are familiar with R and machine learning.

Table of Contents

What You Will Learn

  • Familiarize yourself with deep learning
  • Build the different types of neural networks
  • Learn the advanced topics such as H20 and MXNet

Authors

Table of Contents

Video Details

ISBN 139781788399029
Course Length3 hours
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