An introduction to deep learning and its architectures with real-world use cases
About This Video
- Get a thorough understanding of the Deep Learning architecture and how it's used in the real world
- Get familiar with the different Deep Learning models
- Apply supervised and unsupervised learning to your daily projects
The course starts off with an introduction to Deep Learning and the different tools, hardware, and software before we begin to understand the different training models. We then get to what everyone is talking about: Neural Networks. Here we understand how Neural Networks work and the benefits they offer for supervised and well as unsupervised learning before building our very own neural network. We will then move on to understanding the different Deep Learning Architectures, including how to set up your architecture and align the output. Finally we take a look at Artificial Neural Networks and understand how to build your own ANN.
Taking this course will help you dive head first into the popular field of deep learning as a career choice or for further learning.
This course uses Eclipse 4.7 to run the code samples, while not the latest version available, it provides relevant and informative content on building Artificial Neural Networks using deep learning architecture.
Table of contents
- Chapter 1 : What Is Deep Learning
- Chapter 2 : Neural Networks
- Chapter 3 : Deep Learning Architectures
Chapter 4 : Artificial Neural Network (ANN)
- What Is an Artificial Neural Network? 00:06:38
- How to Build Artificial Neural Network – Prerequisites 00:06:12
- Business Problems Through ANN 00:05:49
- Solutions Through ANN 00:05:53
- Title: Deep Learning Architecture for Building Artificial Neural Networks
- Release date: June 2018
- Publisher(s): Packt Publishing
- ISBN: 9781788395106
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