AI Blueprints

Book description

The essential blueprints and workflow you need to build successful AI business applications

Key Features

  • Learn and master the essential blueprints to program AI for real-world business applications
  • Gain insights into how modern AI and machine learning solve core business challenges
  • Acquire practical techniques and a workflow that can build AI applications using state-of-the-art software libraries
  • Work with a practical, code-based strategy for creating successful AI solutions in your business

Book Description

AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You'll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you'll discover the practical techniques to build AI business applications from first design to full coding and deployment.

The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You'll learn how to approach AI business problems and apply blueprints that can ensure success.

The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a 'trending now' section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers' questions and answer them with relevant responses.

This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you'll also learn how to prepare for future advances in AI. You'll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code.

What you will learn

  • An essential toolbox of blueprints and advanced techniques for building AI business applications
  • How to design and deploy AI applications that meet today's business needs
  • A workflow from first design stages to practical code solutions in your next AI projects
  • Solutions for AI projects that involve social media analytics and recommendation engines
  • Practical projects and techniques for sentiment analysis and helpful chatbots
  • A blueprint for AI projects that recommend products based on customer purchasing habits
  • How to prepare yourself for the next decade of AI and machine learning advancements

Who this book is for

Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.

Publisher resources

Download Example Code

Table of contents

  1. AI Blueprints
    1. Table of Contents
    2. AI Blueprints
      1. Why subscribe?
    3. Foreword
    4. Contributors
      1. About the author
      2. About the reviewer
      3. Packt is searching for authors like you
    5. Preface
      1. Who this book is for
      2. What this book covers
      3. What you need for this book
        1. Download the example code files
        2. Download the color images
        3. Conventions used
      4. Get in touch
        1. Reviews
    6. 1. The AI Workflow
      1. AI isn't everything
      2. The AI workflow
        1. Characterize the problem
          1. Checklist
        2. Develop a method
          1. Checklist
        3. Design a deployment strategy
          1. Checklist
        4. Design and implement a continuous evaluation
          1. Checklist
      3. Overview of the chapters
      4. Summary
    7. 2. A Blueprint for Planning Cloud Infrastructure
      1. The problem, goal, and business case
      2. Method – constraint solvers
        1. OptaPlanner
      3. Deployment strategy
      4. Continuous evaluation
      5. Summary
    8. 3. A Blueprint for Making Sense of Feedback
      1. The problem, goal, and business case
      2. Method – sentiment analysis
      3. Deployment strategy
        1. CoreNLP processing pipeline
        2. Twitter API
        3. The GATE platform
        4. Reddit API
        5. News API
        6. Dashboard with plotly.js and Dash
      4. Continuous evaluation
        1. Retraining CoreNLP sentiment models
      5. Summary
    9. 4. A Blueprint for Recommending Products and Services
      1. Usage scenario – implicit feedback
      2. Content-based recommendations
      3. Collaborative filtering recommendations
        1. BM25 weighting
        2. Matrix factorization
      4. Deployment strategy
      5. Continuous evaluation
        1. Calculating precision and recall for BM25 weighting
        2. Online evaluation of our recommendation system
      6. Summary
    10. 5. A Blueprint for Detecting Your Logo in Social Media
      1. The rise of machine learning
      2. Goal and business case
      3. Neural networks and deep learning
        1. Deep learning
          1. Convolutions
          2. Network architecture
          3. Activation functions
      4. TensorFlow and Keras
      5. YOLO and Darknet
      6. Continuous evaluation
      7. Summary
    11. 6. A Blueprint for Discovering Trends and Recognizing Anomalies
      1. Overview of techniques
      2. Discovering linear trends
        1. Discovering dynamic linear trends with a sliding window
      3. Discovering seasonal trends
        1. ARIMA
        2. Dynamic linear models
      4. Recognizing anomalies
        1. Z-scores with static models
        2. Z-scores with sliding windows
        3. RPCA
        4. Clustering
      5. Deployment strategy
      6. Summary
    12. 7. A Blueprint for Understanding Queries and Generating Responses
      1. The problem, goal, and business case
        1. Our approach
        2. The Pokémon domain
        3. The course advising domain
      2. Method – NLP + logic programming + NLG
        1. NLP with Rasa
        2. Logic programming with Prolog and tuProlog
          1. Prolog unification and resolution
          2. Using Prolog from Java with tuProlog
          3. Pokémon in Prolog
        3. Natural language generation with SimpleNLG
      3. A second example – college course advising
      4. Continuous evaluation
      5. Summary
    13. 8. Preparing for Your Futureand Surviving the Hype Cycle
      1. Always one step ahead
      2. The state of things
        1. Natural language processing
        2. Computer vision
        3. Expert systems and business rules
        4. Planning and scheduling
        5. Robotics
      3. Understanding the hype cycle of AI
      4. The next big thing
      5. Summary
    14. Other Books You May Enjoy
      1. Leave a review - let other readers know what you think
    15. Index

Product information

  • Title: AI Blueprints
  • Author(s): Dr. Joshua Eckroth
  • Release date: December 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781788992879