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Hands-On Neural Networks

You're reading from   Hands-On Neural Networks Learn how to build and train your first neural network model using Python

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781788992596
Length 280 pages
Edition 1st Edition
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Authors (2):
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Leonardo De Marchi Leonardo De Marchi
Author Profile Icon Leonardo De Marchi
Leonardo De Marchi
Laura Mitchell Laura Mitchell
Author Profile Icon Laura Mitchell
Laura Mitchell
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started FREE CHAPTER
2. Getting Started with Supervised Learning 3. Neural Network Fundamentals 4. Section 2: Deep Learning Applications
5. Convolutional Neural Networks for Image Processing 6. Exploiting Text Embedding 7. Working with RNNs 8. Reusing Neural Networks with Transfer Learning 9. Section 3: Advanced Applications
10. Working with Generative Algorithms 11. Implementing Autoencoders 12. Deep Belief Networks 13. Reinforcement Learning 14. Whats Next? 15. Other Books You May Enjoy

GloVe

GloVe stands for Global Vectors and is a model to produce a distributed word representation. It's an unsupervised learning method that finds a useful word representation in a vector space using statistics on the co-occurrence words from a corpus.

It combines two methods: global matrix factorization and local context windows. We will now explain these two models in more detail and show an example of how to use it.

Global matrix factorization

Matrix factorization, also known as matrix decomposition, is the decomposition of a matrix into a product of multiple matrices. There are many ways to decompose a matrix depending on the class of problems we aim to solve.

Matrix factorization is intended as a set of algorithms...

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