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Publisher's Summary

Ready to crank up a neural network to get your self-driving car to pick up the kids from school? Want to add "deep learning" to your LinkedIn profile?
Well, hold on there....
Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Take a step-by-step journey through the basics of neural networks and deep learning, made so simple that...even your granny could understand it!
What you will gain from this audiobook:

A deep understanding of how a neural network and deep learning work
A basics comprehension on how to build a deep neural network from scratch
Who this audiobook is for:

Beginners who want to approach the topic, but are too afraid of complex math to start!
What’s inside?

A brief introduction to machine learning
Two main types of machine learning algorithms
A practical example of unsupervised learning
What are neural networks?
McCulloch-Pitts' neuron
Types of activation function
Types of network architectures
Learning processes
Advantages and disadvantages
Let us give a memory to our neural network
The example of book writing software
Deep learning: the ability of learning to learn
How does deep learning work?
Main architectures and algorithms
Main types of DNN
Available frameworks and libraries
Convolutional neural networks
Tunnel vision
The right architecture for a neural network
Test your neural network
A general overview of deep learning
What are the limits of deep learning?
Deep learning: the basics
Layers, learning paradigms, training, validation
Main architectures and algorithms
Models for deep learning
Probabilistic graphic models
Restricted Boltzmann machines
Deep belief networks
Available frameworks and libraries
Download now!
©2018 Pat Nakamoto (P)2018 Pat Nakamoto
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