文件名称：Apress.Cognitive.Computing.Recipes
文件大小：23.94MB
文件格式：PDF
更新时间：2022-04-20 02:16:55
Congni AI 机器学习
Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries. Along with an overview of the contemporary technology landscape, Machine Learning and Deep Learning with Cognitive Computing Recipes covers the business case for machine learning and deep learning. Covering topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation this book offers a comprehensive toolkit that you can apply quickly and easily in your own projects. With its focus on Microsoft Cognitive Services offerings, you’ll see recipes using multiple different environments including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. What You Will Learn Build production-ready solutions using Microsoft Cognitive Services APIs Apply deep learning using TensorFlow and Microsoft Cognitive Toolkit (CNTK) Solve enterprise problems in natural language processing and computer vision Discover the machine learning development life cycle – from formal problem definition to deployment at scale Who This Book Is For Software engineers and enterprise architects who wish to understand machine learning and deep learning by building applications and solving real-world business problems. 使用完整的实际代码示例解决您的AI和机器学习问题。本书使用问题解决方法，通过提供认知服务API，机器学习平台和库等工具的组合，使日常开发人员可以访问深度学习和机器学习。 除了对当代技术领域的概述外，机器学习和深度学习与认知计算食谱涵盖了机器学习和深度学习的商业案例。本书涵盖了数字助理，计算机视觉，文本分析，语音和机器人过程自动化等主题，提供了一个全面的工具包，您可以在自己的项目中快速轻松地应用。通过关注Microsoft认知服务产品，您将看到使用多种不同环境（包括TensowFlow和CNTK）的配方，为您提供更深入的深度学习生态系统视角。 你将学到什么 使用Microsoft Cognitive Services API构建生产就绪解决方案 使用TensorFlow和Microsoft Cognitive Toolkit（CNTK）应用深度学习 解决自然语言处理和计算机视觉中的企业问题 发现机器学习开发生命周期 - 从正式的问题定义到大规模部署 本书适用于谁 希望通过构建应用程序和解决实际业务问题来了解机器学习和深度学习的软件工程师和企业架构师。