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Hands-On Machine Learning on Google Cloud Platform

You're reading from  Hands-On Machine Learning on Google Cloud Platform

Product type Book
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Pages 500 pages
Edition 1st Edition
Languages
Authors (3):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
V Kishore Ayyadevara V Kishore Ayyadevara
Profile icon V Kishore Ayyadevara
Alexis Perrier Alexis Perrier
Profile icon Alexis Perrier
View More author details

Table of Contents (18) Chapters

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine 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

Magenta

On June 1, 2016, Google launched the Magenta project, a research project that aims to allow the creation of art and music in an autonomous way through the use of AI. Based on the TensorFlow platform, Magenta aims to publish code in open source mode on GitHub to allow developers to achieve increasingly striking and advanced results.

The project is a brainchild of the Google Brain team, a deep learning AI research team at Google. It combines open-ended machine learning research with system engineering and Google-scale computing resources.

The Magenta project has set itself two ambitious goals: to develop machine learning for art and music, and to build a community of people interested in this topic. Machine learning has long been used in different contexts, in particular for speech recognition and translation of languages. Magenta was created to concentrate activity on...

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