Machine Learning for Designers

Table of contents

1. Machine Learning for Designers
   1. Introduction
   2. Why Design for Machine Learning is Different
      1. A Different Kind of Logic
      2. A Different Kind of Development
      3. A Different Kind of Precision
      4. A Different Kind of Problem
   3. What Is Machine Learning?
      1. The Mental Process of Recognizing Objects
      2. Learning by Example
      3. Mechanical Induction
      4. Common Analogies for Machine Learning
      5. Ways of Learning
      6. What Is Deep Learning?
   4. Enhancing Design with Machine Learning
      1. Parsing Complex Information
      2. Enabling Multimodal User Input
      3. New Modes of Input
      4. Creating Dialogue
      5. Designing Building Blocks
      6. Acquiring Training Data
      7. The Intelligence Feedback Loop
   5. Dealing with Challenges
      1. Designing for Uncertainty
      2. Mitigating Faulty Assumptions
      3. Creating Sanity Checks
   6. Working with Machine Learning Platforms
      1. Machine-Learning-as-a-Service Platforms
      2. Open Source Machine Learning Toolkits
      3. Fully Customized Machine Learning Tools
      4. Machine Learning Prototyping Tools
      5. Incorporating Machine Learning into Design Processes
   7. Conclusions
   8. Going Further
      1. Staying Up-to-date with Advancements in the Field
      2. Resources for Further Study of Machine Learning
      3. Technical Resources