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- Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
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Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
Ebook
Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples.
You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks.
By the end of this book, you will be able to solve real-world problems quickly with deep neural networks.
You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best practices and safe choices to help readers make the right decision while training deep neural networks.
By the end of this book, you will be able to solve real-world problems quickly with deep neural networks.
- 1. The Building Blocks of Deep Learning
- 2. Using Deep Learning To Solve Regression Problems
- 3. Monitoring Network Training Using Tensor Board
- 4. Using Deep Learning To Solve Binary Classification Problems
- 5. Using Keras To Solve MultiClass Classification Problems
- 6. HyperParameter Optimization
- 7. Training a CNN From Scratch
- 8. Transfer Learning with Pretrained CNNs
- 9. Training an RNN from scratch
- 10. Training LSTMs with Word Embeddings From Scratch
- 11. Training Seq2Seq Models
- 12. Using Deep Reinforcement Learning
- 13. Deep Convolutional Generative Adversarial Networks
- Title: Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
- Author: Mike Bernico
- Original title: Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
- ISBN: 9781788838917, 9781788838917
- Date of issue: 2018-03-09
- Format: Ebook
- Item ID: e_152s
- Publisher: Packt Publishing