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Mastering TensorFlow 1.x

You're reading from   Mastering TensorFlow 1.x Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788292061
Length 474 pages
Edition 1st Edition
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Toc

Table of Contents (21) Chapters Close

Preface 1. TensorFlow 101 FREE CHAPTER 2. High-Level Libraries for TensorFlow 3. Keras 101 4. Classical Machine Learning with TensorFlow 5. Neural Networks and MLP with TensorFlow and Keras 6. RNN with TensorFlow and Keras 7. RNN for Time Series Data with TensorFlow and Keras 8. RNN for Text Data with TensorFlow and Keras 9. CNN with TensorFlow and Keras 10. Autoencoder with TensorFlow and Keras 11. TensorFlow Models in Production with TF Serving 12. Transfer Learning and Pre-Trained Models 13. Deep Reinforcement Learning 14. Generative Adversarial Networks 15. Distributed Models with TensorFlow Clusters 16. TensorFlow Models on Mobile and Embedded Platforms 17. TensorFlow and Keras in R 18. Debugging TensorFlow Models 19. Tensor Processing Units
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Airline Passengers dataset

For the sake of brevity and simplicity, we selected a very small dataset called International Airline Passengers (airpass). The data contains the number of total passengers every month, from January 1949 to December 1960. The numbers in the dataset refer to the amount in thousands. This dataset was originally used by Box and Jenkins in their work in 1976. It was collected as part of TimeSeries Dataset Library (TSDL) along with various other time series datasets by Professor Rob Hyndman at Monash University, Australia. Later, the TSDL was moved to DataMarket (http://datamarket.com).

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