Neural Networks in Machine Learning for Developers [Video]

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Neural Networks in Machine Learning for Developers [Video]



Enhance your knowledge of Neural Networks
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Video Details

ISBN 139781789139792
Course Length44 minutes

Video Description

Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the Globe is, "How do I get started in Machine Learning?" One reason could be the vastness of the subject area because people often get overwhelmed by the abstractness of ML and terms such as regression, supervised learning, probability density function, and so on. This systematic guide will teach you various Machine Learning techniques.

You will start with the very basics of neural networks and types. Then we learn about powerful variations in neural networks and Recurrent Neural Networks. Finally, we conclude with a synthetic introduction to more advanced Machine Learning techniques, such as GANs and reinforcement learning.

Style and Approach

This course gives you a glimpse into Machine Learning Models and the application of models at scale using clustering, classification, regression, and reinforcement learning, all with fun examples. Hands-on examples are presented to help you understand the power of problem-solving with Machine Learning and advanced architectures, software installation, and configuration.

Table of Contents

Neural Networks
The Course Overview
History of Neural Models
Implementing a Simple Function
Loss Function
Convolutional Neural Networks
Origin of Convolutional Neural Networks
Implementing Discrete Convolution
Deep Neural Networks
Recurrent Neural Networks
RNNs
LSTM
Univariate Time Series Prediction
Recent Models and Developments
GANs
Reinforcement Learning

What You Will Learn

  • Learn the math and mechanics of Machine Learning via a developer-friendly approach
  • Prepare yourself and other developers for working in the new, ubiquitous field of Machine Learning
  • Get an overview of the most well known and powerful tools to solve computing problems using Machine Learning.
  • Get an intuitive and down-to-earth introduction 
  • Apply the concepts to interesting and cutting-edge problems.

Authors

Table of Contents

Neural Networks
The Course Overview
History of Neural Models
Implementing a Simple Function
Loss Function
Convolutional Neural Networks
Origin of Convolutional Neural Networks
Implementing Discrete Convolution
Deep Neural Networks
Recurrent Neural Networks
RNNs
LSTM
Univariate Time Series Prediction
Recent Models and Developments
GANs
Reinforcement Learning

Video Details

ISBN 139781789139792
Course Length44 minutes
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