Table of Contents
Preface
Part 1 – Introduction to TensorFlow
1
Introduction to Machine Learning
What is ML?
Types of ML algorithms
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforcement Learning
ML life cycle
The business case
Data gathering and understanding
Modeling
Error analysis
Model deployment and monitoring
Exploring ML use cases
Healthcare
The retail industry
The entertainment industry
Education
Agriculture
Introducing the learning journey
Why take the exam?
What is the exam all about?
How to ace the exam
When to take the exam
Exam tips
What to expect after the exam
Summary
Questions
Further reading
2
Introduction to TensorFlow
Technical requirements
What is TensorFlow?
Setting up our environment
Data representation ...
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