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Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python


Free Shipping Included! Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python by Unknown at EMS Linux. Hurry! Limited time offer. Offer valid only while supplies last. Key FeaturesImplement various deep learning algorithms in Keras and see how deep learning can be used in gamesSee how various deep learning models


Product Description

Key Features

  • Implement various deep learning algorithms in Keras and see how deep learning can be used in games
  • See how various deep learning models and practical use cases can be implemented using Keras
  • A practical, hands-on guide with real-world examples to give you a strong foundation in Keras

Book Description

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer.

Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks.

What you will learn

  • Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm
  • Fine-tune a neural network to improve the quality of results
  • Use deep learning for image and audio processing
  • Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases
  • Identify problems for which Recurrent Neural Network (RNN) solutions are suitable
  • Explore the process required to implement Autoencoders
  • Evolve a deep neural network using reinforcement learning

Who This Book Is For

If you're a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep learning with Keras. A knowledge of Python is required for this book.

Table of Contents

  1. Neural Networks Foundations
  2. Keras Installation and API
  3. Deep Learning with ConvNets
  4. Generative Adversarial Networks and WaveNet
  5. Word Embeddings
  6. Recurrent Neural Networks - RNNs
  7. Additional Deep Learning Models
  8. AI Game Playing

Additional Information

Manufacturer:Packt Publishing - ebooks Account
Brand:Unknown
Publisher:Packt Publishing - ebooks Account
Studio:Packt Publishing - ebooks Account
EAN:9781787128422
Item Size:0.72 x 9.25 x 9.25 inches
Package Weight:1.25 pounds
Package Size:7.52 x 0.98 x 0.98 inches

Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python by Unknown

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Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python

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