Publisher: K-i-s-publishing

Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks

Karthiek Reddy Bokka, Shubhangi Hora , Tanuj...

Deep Learning for Time Series Cookbook. Use PyTorch and Python recipes for forecasting, classification, and anomaly detection

Vitor Cerqueira, Luís Roque

Deep Learning from the Basics. Python and Deep Learning: Theory and Implementation

Koki Saitoh, Shigeo Yushita

Deep Learning: Practical Neural Networks with Java. Build and run intelligent applications by leveraging key Java machine learning libraries

Alan M. F. Souza, Fabio M. Soares,...

Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Mike Bernico

Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++

Bill Chen, Vikash Gupta

Deep Learning with fastai Cookbook. Leverage the easy-to-use fastai framework to unlock the power of deep learning

Mark Ryan

Deep Learning with Hadoop. Distributed Deep Learning with Large-Scale Data

Dipayan Dev

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

Antonio Gulli, Sujit Pal

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework

Willem Meints

Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet

Andrés P. Torres, Paul Newman

Deep Learning with PyTorch. A practical approach to building neural network models using PyTorch

Vishnu Subramanian

Deep Learning with PyTorch Lightning. Swiftly build high-performance Artificial Intelligence (AI) models using Python

Kunal Sawarkar, Dheeraj Arremsetty

Deep Learning with PyTorch Quick Start Guide. Learn to train and deploy neural network models in Python

David Julian

Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x

Swarna Gupta, Rehan Ali Ansari, Dipayan Sarkar

Deep Learning with R for Beginners. Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet

Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden)...

Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition

Antonio Gulli, Dr. Amita Kapoor, Sujit Pal

Deep Learning with TensorFlow and Keras - 3rd edition. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition

Dr. Amita Kapoor, Antonio Gulli, Sujit Pal

Deep Learning with TensorFlow. Explore neural networks and build intelligent systems with Python - Second Edition

Giancarlo Zaccone, Vihan Jain, Md. Rezaul Karim,...

Deep Learning with TensorFlow. Explore neural networks with Python

Giancarlo Zaccone, Fabrizio Milo, Md. Rezaul Karim

Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently

Christopher Bourez

Deep Reinforcement Learning Hands-On. A practical and easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF - Third Edition

Maxim Lapan

Deep Reinforcement Learning Hands-On. Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more - Second Edition

Maxim Lapan

Deep Reinforcement Learning Hands-On. Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Oleg Vasilev, Maxim Lapan, Martijn van Otterlo,...