Mastering OpenCV with Practical Computer Vision Projects pdf

文件参考冈萨雷斯_数字图像处理第三版，包括实验项目的介绍和第三章实验项目试题的参考代码

作者: Alex Gonzalez 出版社: Packt Publishing 副标题: Over 70 hands-on recipes for professional embedded Linux developers to optimize and boost their Yocto know-how 出版年: 2015-3-31 页数: 225 定价: USD 44.99 装帧: Paperback ISBN: 9781784395186

鉴于Visual Studio 2017的工具-扩展和更新经常搜不到 Install Projects工具，因此放在这里方便大家下载，VSIX格式。安装方法示例：命令提示符下D:\Program Files (x86)\Microsoft Visual Studio\2017\Community\Common7\IDE\VSIXInstaller.exe+空格+VSIX文件绝对路径带文件名称，即可安装。

Book Description: A straightforward, visual guide that shows young learners how to build their own computer projects using Scratch, a popular free programming language, using fun graphics and easy-to-follow instructions. Kids can animate their favorite characters, build games to play with friends, create silly sound effects, and more with Coding Projects in Scratch. All they need is a desktop or laptop with Adobe 10.2 or later, and an internet connection to download Scratch 2.0. Coding can be done without download on https://scratch.mit.edu. Step-by-step instructions teach essential coding basics and outline 18 fun and exciting projects, including a personalized birthday card; a "tunnel of doom" multiplayer game; a dinosaur dance party animation with flashing lights, music, and dance moves—and much more. The simple, logical steps in Coding Projects in Scratch are fully illustrated with fun pixel art and build on the basics of coding, so that kids can have the skills to make whatever kind of project they can dream up. Supporting STEM education initiatives, computer coding teaches kids how to think creatively, work collaboratively, and reason systematically, and is quickly becoming a necessary and sought-after skill. DK's computer coding books are full of fun exercises with step-by-step guidance, making them the perfect introductory tools for building vital skills in computer programming.

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