Keras

Packt, 2018. — 288 p. Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library....

Packt Publishing, 2019. — 316 р. — ISBN: 978-1789136678. Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for...

Packt Publishing, 2018. — 368 p. — ASIN B078N8RDCP. A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs,...

Packt Publishing, 2017. — 318 p. — ISBN: 978-1-78712-842-2. Get to grips with the basics of Keras to implement fast and efficient deep-learning models 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...

Apress, 2019. — 182 p. Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with...

3rd ed. — Packt, 2020. — 495 p. — ISBN: 978-1800562967. Discover how to leverage Keras, the powerful and easy-to-use open-source Python library for developing and evaluating deep learning models Key Features Get to grips with various model evaluation metrics, including sensitivity, specificity, and AUC scores Explore advanced concepts such as sequential memory and sequential...

Packt Publishing, 2019. — 412 p. — ISBN 978-1-83855-507-8. Though designing neural networks is a sought-after skill, it is not easy to master. With Keras, you can apply complex machine learning algorithms with minimum code. Applied Deep Learning with Keras starts by taking you through the basics of machine learning and Python all the way to gaining an in-depth understanding of...

Amazon Digital Services LLC, 2018. — 189 р. This introduction will help you develop a good understanding of deep learning completely from scratch This book covers: Introduction to machine learning and deep learning Math for deep learning explained to the layman How neural networks work: a general overview Activation functions in deep networks Loss functions Weight...

2nd Edition. — Packt Publishing, 2020. — 444 p. — ISBN: 978-1-83921-757-9. Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming You already know that you want to learn Keras, and a smarter way to learn is to learn by doing. The Deep Learning with Keras Workshop focuses on building up your practical skills...

Reactive Publishing, 2024. — 654 p. In an era where Artificial Intelligence is revolutionizing industries, mastering the tools and techniques to harness its potential is essential. Mastering Keras: Building Advanced Deep Learning Models with Python is your comprehensive guide to diving deep into the world of neural networks and Deep Learning using Keras, one of the most...

Independently published, 2021. — 68 p. — ASIN : B0947GKFSZ. This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression, and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition, and much...