Designing with ML
Learn How to Build Usable Machine Learning Applications
Machine learning can enable new capabilities that provide value to users and offer strong product differentiation. However, achieving these goals often requires a focus beyond practices for collecting and managing data, building, training, evaluating and deploying models ( MLOps ). As ML becomes more democratized, the user experience will play a more important role compared to core model capabilities. Using end-to-end examples, Designing with ML explores how a user centered design approach (DesignOps) can help align MLOps efforts with end user goals and business objectives.

A book by
Victor Dibia, PhD

Chapter Guide
Current proposed table of content for the designingwithml book is shown below. Note that parts of this may change as the book is developed.
1
Introduction
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2
Machine Learning Fundamentals
3
Introduction to Tensorflow
4
Your First Machine Learning Application - Taxi Advisor
5
What You Need to Know to Build ML Applications
6
Machine Learning and Human Centered Design
7
Planning Your Machine Learning Project
8
Responsible AI
9
Machine Learning Systems Design Use Cases
10
Tensorflow Labs
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