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Hands-On Machine Learning on Google Cloud Platform

You're reading from   Hands-On Machine Learning on Google Cloud Platform Implementing smart and efficient analytics using Cloud ML Engine

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Length 500 pages
Edition 1st Edition
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Authors (3):
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Alexis Perrier Alexis Perrier
Author Profile Icon Alexis Perrier
Alexis Perrier
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (18) Chapters Close

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine FREE CHAPTER 3. Google Cloud Storage 4. Querying Your Data with BigQuery 5. Transforming Your Data 6. Essential Machine Learning 7. Google Machine Learning APIs 8. Creating ML Applications with Firebase 9. Neural Networks with TensorFlow and Keras 10. Evaluating Results with TensorBoard 11. Optimizing the Model through Hyperparameter Tuning 12. Preventing Overfitting with Regularization 13. Beyond Feedforward Networks – CNN and RNN 14. Time Series with LSTMs 15. Reinforcement Learning 16. Generative Neural Networks 17. Chatbots

Convolutional neural networks

ANN is a family of models inspired from biological neural networks (the human brain) that, starting from the mechanisms regulating natural neural networks, plan to simulate human thinking. They are used to estimate or approximate functions that may depend on a large number of inputs, many of which are often unknown. ANNs are generally presented as interconnected neuron systems among which an exchange of messages takes place. Each connection has a related weight; the value of the weight is adjustable based on experience, and this makes neural networks an instrument adaptable to the various types of input and having the ability to learn.

ANNs define the neuron as a central processing unit, which performs a mathematical operation to generate one output from a set of inputs. The output of a neuron is a function of the weighted sum of the inputs plus the...

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