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ProductizeML
Introduction
Objectives
About the Course
Guidelines
Syllabus
After Completion
Machine Learning
Why ML, and why now
Supervised Learning
Unsupervised Learning
Deep Learning
ML Terminology
Data Management
Data Access
Data Collection
Data Curation
Train and Evaluate
Framework and Hardware
Training Neural Networks
Model Evaluation
Productize It
ML Life Cycle
Business Objectives
Data Preparation
Model Development
Train, Evaluate, and Deploy
A/B Testing
KPI Evaluation
PM Terminology
Resources
Readings
Courses
Videos
Hands-On
Python for Machine Learning
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Readings

Required Readings

Name
Author(s)
Publisher
Year
Martin Zinkevich
Google
2020
People + AI Research (PAIR)
Google
2020
Apple's WWDC 2019
Apple
2019
V.M. Megler
Amazon Web Services
2019
​DJ Patil​
First Round
​
Benedict Evans
​
2018
Synthesized
Synthesized
2020
Yavel Gavish
Medium
2017

Interesting readings

Name
Author(s)
Publisher
Year
Trey Causey
Medium
2017
Justin Norman, Peter Skomoroch and Mike Loukides
O'Reilly
2020
Matt Fyles
​
​
Peter Skomoroch and Mike Loukides
O'Reilly
2020
Nisha Talagala
Oracle
2019
Brendan Fortuner
​
2020
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Courses
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Contents
Required Readings
Interesting readings