Pragmatic AI : an intoduction to cloud-basd machine learning
著者
書誌事項
Pragmatic AI : an intoduction to cloud-basd machine learning
(Addison Wesley data & analytics series)
Addison-Wesley, c2019
- : pbk
大学図書館所蔵 全4件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes index
内容説明・目次
内容説明
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning
Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results-even if you don't have a strong background in math or data science.
Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you'll gain a more intuitive understanding of what you can achieve with them and how to maximize their value.
Building on these fundamentals, you'll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you're a business professional, decision-maker, student, or programmer, Gift's expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment.
Get and configure all the tools you'll need
Quickly review all the Python you need to start building machine learning applications
Master the AI and ML toolchain and project lifecycle
Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn
Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems
Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services
Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more
Work with Microsoft Azure AI APIs
Walk through building six real-world AI applications, from start to finish
Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
目次
Foreword
Preface
Acknowledgments
About the Author
Part I: Introduction to Pragmatic AI
Chapter 1: Introduction to Pragmatic AI
Chapter 2: AI and ML Toolchain
Chapter 3: Spartan AI Lifecycle
Part II: AI in the Cloud
Chapter 4: Cloud AI Development with Google Cloud Platform
Chapter 5: Cloud Ai Development with Amazon Web Services
Part III: Creating Practical AI Applications from Scratch
Chapter 6: Predicting Social-Media Influence in the NBA
Chapter 7: Creating an Intelligent Slackbot on AWS
Chapter 8: Finding Project Management Insights from a Github Organization
Chapter 9: Dynamically Optimizing EC2 Instances on AWS
Chapter 10: Real Estate
Chapter 11: Production AI for User Generated Content (UGC)
Appendix A: AI Accelerators
Appendix B: Deciding on Cluster Size
Index
「Nielsen BookData」 より