This book is to explore and explain the strategically sound capabilities at the synchronization between quantum computing and artificial intelligence …
Link to the GitHub Repository containing the code examples and additional material:https://github.com/rasbt/python-machi...Many of the most innovative breakthroughs and exciting new …
Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the …
This book from the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep …
I was looking for this book badly, so I understand the need. Please read with your heart and support him …
Master Deep Learning with this fun, practical, hands on guide. With the explosion of big data deep learning is now …
Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and …
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the …
Master Deep Time Series Forecasting with Python! Deep Time Series Forecasting with Python takes you on a gentle, fun and …
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to …
Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This …
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document …
This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and …
Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and …
Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help …
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Key …
Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins …
This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop …
Deep learning is a committed approach to learning. It is a process of constructing and interpreting new knowledge in light …
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus …
Can machine learning deliver AI? Theoretical results, inspiration from the brain and cognition, as well as machine learning experiments suggest …
Master Data Science and Machine Learning with Linear Regression and Logistic Regression in Python (Machine Learning in Python)
Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the …
The remarkable progress in computer vision over the last few years is, by and large, attributed to deep learning, fueled …
Whether you're a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist …
Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. In Deep Learning with JAX …
In Deep Learning with JAX you will learn how to • Use JAX for numerical calculations • Build differentiable models …
