Pragmatic AI: An Introduction to Cloud-Based Machine Learning

About

Features

• Illuminates the latest solutions from Google, Amazon, and Microsoft, plus powerful techniques based on Python and R
• Real-world examples and workflows show how machine learning, AI, and cloud computing come together in real business solutions
• Covers every step from deployment to production, focusing on cloud environments that maximise scalability and simplify deployment
• Addresses coding, libraries, statistical techniques, modeling for fast prototyping, and more

Description

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

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Sample Content

Table of Contents

• 1. Introduction to Pragmatic AI
• 2. Get Tools and Set Them Up
• 3. Overview of Lifecycle
• 4. Using Cloud Machine Learning Services
• 5. Using AWS AI Services
• 6. Cognitive Services API
• 7. Finding Signals in Facebook, Twitter and Wikipedia
• 8. Write a Slack Bot that Runs on AWS Lambda (Serverless) and Listens to a Channel
• 9. Retrieve Data from Twitter API and Extract Follower Relationships
• 10. Identify Patterns of Highly Productive Developers (and Learn How to Find Similarly Productive Developers)
• 11. Call EC2 Price AP
• 12. Forecasting Current and Future Sales Price of a Home Using Zillow
• Glossary
• Appendices

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