Overview
Syllabus
Intro
About the Speaker
Why This Talk?
Is a Highly Accurate Model Always Desirable?
The 'Data' Question
The 'Metric' Question
The 'Repeatability Question
The 'Business' Question
The 'Impact' Question
Modern ML Tools - A Blessing or a Curse?
Machine Learning Model Life Cycle
What is your biggest pain point?
Data beats algorithm
Dispelling a Common Myth
The 80/20 rule
Beg, borrow and steal
Building the model is only a small piece of the puzzle
The Importance of Data
Predictability of your model
Further Evaluation Data Set
Increasing the exposure of your model
Taught by
Data Science Dojo