1. Practical Deep Learning for Cloud, Mobile, and Edge
Authors: Anirudh Koul, Siddha Ganju, Meher Kasam
This book serves as an essential guide for anyone looking to delve into the world of deep learning. With hands-on projects that leverage cloud, mobile, and edge computing, it provides real-world applications of AI that are invaluable. Written by leading experts in the field, it focuses on Python, Keras, and TensorFlow, ensuring that you learn from the best practices in modern machine learning. Understanding how to deploy deep learning models across various platforms will set you apart in a competitive job market. Don’t miss out on the chance to equip yourself with cutting-edge skills that drive innovation.
2. Künstliche Intelligenz und Maschinelles Lernen
Author: Marco Nitschke
This German edition delves into the comparison of deep learning frameworks such as TensorFlow, Keras, PyTorch, CNTK, and MXNet. If you are a German speaker looking to bridge the gap between theoretical knowledge and practical application, this book is an excellent choice. It not only outlines the capabilities of each framework but also provides insights into their strengths and weaknesses, which is crucial for making informed decisions in your projects.
3. Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide
Author: Willem Meints
This practical guide is a gateway to building neural networks using Microsoft’s Cognitive Toolkit. It emphasizes a quick-start approach that eases newcomers into the complexities of deep learning. With step-by-step instructions and essential examples, it’s the perfect resource for developers eager to harness Microsoft’s powerful AI framework. This book is ideal for those already familiar with programming and looking to expand their skill set into AI and deep learning.
