Machine Learning Sucks

Explore the challenges and pitfalls of machine learning in this 36-minute conference talk by Dr. Pieter Buteneers from Chatlayer.ai at ML Conference 2018 Spring. Delve into common mistakes in implementing machine learning algorithms and learn strategies to avoid them. Gain insights on turning ML into sustainable business practices, understanding data issues, preventing overfitting, and addressing extrapolation problems. Examine the impact of feature selection, adversarial examples, and technological advancements on ML applications. Discuss the implications of machine learning on job markets, democracy, and startups. Despite its difficulties, discover the amazing potential of machine learning and how to navigate its complexities in various business contexts.

Intro
Machine Learning Sucks
Data
Over-fitting
Extrapolation
Features
Adverserial Examples
Technology
Job market
Democracy
Start-ups
Business
Conclusion
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