This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning, and how to utilize the TensorFlow library to rapidly build powerful ML models. You’ll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges such as call center volume prediction and sen...(展开全部)

We're living in a big data world. Being able to make near-real-time decisions becomes increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning applications? The answer is TensorFlow, a new open sour...(展开全部)

Key Features Bored of too much theory on TensorFlow? This book is what you need! Thirteen solid projects and four examples teach you how to implement TensorFlow in production. This example-rich guide teaches you how to perform highly accurate and efficient numerical computing with TensorFlow It is a practical and methodically explained guide that allows you to apply Tensorflow’...(展开全部)

Key Features Bored of too much theory on TensorFlow? This book is what you need! Thirteen solid projects and four examples teach you how to implement TensorFlow in production. This example-rich guide teaches you how to perform highly accurate and efficient numerical computing with TensorFlow It is a practical and methodically explained guide that allows you to apply Tensorflow’...(展开全部)

作者简介： Willi Richert 机器学习和机器人学博士，目前任职于微软Bing搜索核心研发团队。他从事多种机器学习领域的研究，包括主动学习和统计机器翻译。 Luis Pedro Coelho 计算生物学家，主要关注生物图像信息学和大规模图像数据的处理，致力于生物标本图像分析中机器学习技术的应用，他还是Python计算机视觉库mahotas的主要开发人员。他于1998年开始开发开源软件，2004年起从事Python开发，并为多个Python开源库贡献了代码。另外，Luis拥有机器学习领域世界领先的卡内基-梅隆大学的博士学位，并发表过多篇科学论文。 译者简介： 刘峰 百度LBS地图基础业务部资深研发工程师，新加坡南洋理工大学计算机工程系博士，研究领域包括机器学习、模糊神经网络等。2010年加入百度，主要从事大数据分析和挖掘方面的工作，近年来专注于...(展开全部)

TensorFlow.js is a framework that enables you to create performant machine learning (ML) applications that run smoothly in a web browser. With this book, you will learn how to use TensorFlow.js to implement various ML models through an example-based approach.Starting with the basics, you'll understand how ML models can be built on the web. Moving on, you will get to grips with the TensorFlow.js ecosystem to develop applications more efficiently. The book will then guide you through implementing ML techniques and algorithms such as regression, clustering, fast Fourier transform (FFT), and dimensionality reduction. You will later cover the Bellman equation to solve Markov decision process (MDP) problems and understand how it is related to reinforcement learning. Finally, you will explore techniques for deploying ML-based web applications and training models with TensorFlow Core. Throughout this ML book, you'll discover useful tips and tricks that will build on your knowledge.By the end of this book, you will be equipped with the skills you need to create your own web-based ML applications and fine-tune models to achieve high performance.

Joel Lawhead 目前是NVision公司的CIO，该公司是业内屡获殊荣的地理信息集成和传感工程服务提供商。他还获得了管理专业人员资格认证（Project Management Professional，PMP)，地理信息专业资格认证(certified GIS Professional ，GISP)。 Joel于1997年开始使用Python，从2000年开始使用它进行地理空间软件的开发，也是Learning Geospatial Analysis with Python（第1版）和QGIS Python Programming Cookbook的作者，并且这两本书都是Packt出版的。他撰写的Python Cookbook系列图书由O'Reilly Media出版，其不同版本更是各具特色。除此之外，他还是广受赞誉的开源软件PyShp（Py...(展开全部)

If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages.