Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow Key Features Build TensorFlow-powered AI applications for mobile and embedded devices Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning Get practical insights and exclusive working code not available in the TensorFlow documentation Book Description As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You'll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips. What you will learn Classify images with transfer learning Detect objects and their locations Transform pictures with amazing art styles Understand simple speech commands Describe images in natural language Recognize drawing with Convolutional Neural Network and Long Short-Term Memory Predict stock price with Recurrent Neural Network in TensorFlow and Keras Generate and enhance images with generative adversarial networks Build AlphaZero-like mobile game app in TensorFlow and Keras

This book is your guide to fast gradient boosting in Python. You will discover the XGBoost Python library for gradient boosting and how to use it to develop and evaluate gradient boosting models. In this book you will discover the techniques, recipes and skills with XGBoost that you can then bring to your own machine learning projects. Gradient Boosting does have a some fascinating math under the covers, but you do not need to know it to be able to pick it up as a tool and wield it on important projects to deliver real value. From the applied perspective, gradient boosting is quite a shallow field and a motivated developer can quickly pick it up and start making very real and impactful contributions.

OpenCV_ Computer Vision Projects with Python.PDF------------------------------------------------

Building Machine Learning Projects with TensorFlow 英文无水印pdf pdf使用FoxitReader和PDF-XChangeViewer测试可以打开

数字图像处理（MATLAB版）（第二版）配套资源包，包括dipum_toolbox_p_latest 工具箱，书中用到的原始图片，案例工程

This is a book about building Arduino-powered devices for everyday use, and then connecting those devices to the Internet. If you're one of the many who have decided to build your own Arduino-powered devices for IoT applications, you've probably wished you could find a single resource - a guidebook for the eager-to-learn Arduino enthusiast - that teaches logically, methodically, and practically how the Arduino works and what you can build with it. Building Arduino Projects for the Internet of Things: Experiments with Real-World Applications is exactly what you need. Written by a software developer and solution architect who got tired of hunting and gathering various lessons for Arduino development as he taught himself all about the topic, this book gives you an incredibly strong foundation of Arduino-based device development, from which you can go in any direction according to your specific development needs and desires. Readers are introduced to the building blocks of IoT, and then deploy those principles to by building a variety of useful projects. Projects in the books gradually introduce the reader to key topics such as internet connectivity with Arduino, common IoT protocols, custom web visualization, and Android apps that receive sensor data on-demand and in realtime. IoT device enthusiasts of all ages will want this book by their side when developing Android-based devices.

Mastering OpenCV with Practical Computer Vision Projects .pdf，是2014年的最新书籍，写的很好，对使用opencv做图像的很有帮助。