Understanding and coding complicated deep studying algorithms with the main intuitive deep studying library in existence
- A entire and up to date creation to GANs
- A whole assessment of Keras
- A dive into complex deep studying sticking to the basic mathematics
Keras allows a brand new new release of deep studying builders to entry the whole energy of TensorFlow at the one hand, whereas focusing on development purposes at the different. much more astonishing is the facility to put in writing purposes drawing from the ability of latest algorithms, with no really having to enforce all of the algorithms, due to the fact they're already available.
After introducing Keras and familiarizing the reader with Keras through classical deep studying algorithms, Dr. Atienza walks the developer via autoencoders first. he is taking the strategy of creating on fairly famous techniques and algorithms, ahead of introducing newer advancements to operating builders. He then asks the reader to jot down and comprehend an NLP software to turn out the sensible price of autoencoders written with Keras.
The middle of the ebook lies within the insurance of a number of sessions of hostile networks (GANs). Dr. Atienza specializes in the newest successes of GANs and teaches builders to enforce more moderen effects for themselves, caution them of pitfalls and displaying them the benefits of every one. He focuses particularly on snapshot iteration and synthesis.
Finally, the booklet finishes with an advent to reinforcement studying, utilizing OpenAI fitness center as a framework to simplify experimenting with a number of regulations and algorithms. back, Keras is the unifying layer during which OpenAI health club is accessed.
Overall, complex Keras exhibits the complete functions of Keras to a developer, whereas attempting to steer clear of taking a look at underlying infrastructure supplied through TensorFlow, Theano or Microsoft Cognitive prone. Dr. Atienza is exhibiting tips on how to get new algorithms to paintings inside Keras, with no getting the reader tangled in too many implementation details.
What you are going to learn
- You will study Keras thoroughly
- To code picture synthesis examples with GANs
- To distinguish a number of forms of adverse networks and enforce them
- To write a reinforcement studying software with OpenAI gym
- To step clear of vintage deep studying and laptop studying and write production-ready functions according to contemporary research
Who This publication Is For
Familiarity with Python and easy desktop studying is important for this e-book and it might be finest if the reader had understood numerous easy deep studying algorithms, like CNNs and RNNs.
About the Author
Professor Rowel Atienza is an affiliate professor on the collage of the Philippines, Diliman, that is normally considered as the top collage of the rustic. He has a PhD from Australian nationwide college. His examine components comprise robotics, imaginative and prescient, photographs, language processing and realizing, and VR/AR, and he has written approximately images, digital fact, and the human-robot interface. he's additionally well-published in deep learning.
This is his first e-book for the broader developer community.
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Extra resources for Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world
Advanced Deep Learning with Keras: Applying GANs and other new deep learning algorithms to the real world