Machine Learning in the Real World

Explore the practical challenges of implementing machine learning in real-world scenarios through this insightful conference talk from NDC Copenhagen 2022. Delve into the complexities that arise before reaching the stage of applying machine learning algorithms. Examine issues such as handling missing and incorrect data, understanding the trade-offs between precision and accuracy, and grasping the importance of conditional probabilities. Learn how physical constraints, like the Earth's curvature, can impact data analysis. Investigate the business aspects of machine learning projects, including cost considerations, risk assessment, and managing shifting expectations. Gain valuable insights into time service analysis and various use cases. This presentation goes beyond theoretical concepts, offering practical knowledge for professionals looking to navigate the challenges of real-world machine learning implementation.

Introduction
Missing data
One minute updates
Incorrect data
The hump
Precision vs accuracy
Quiz
Conditional Probabilities
Time
Physics
Business Case
Conclusion
Question of cost
Risk aversion
Shifting expectations
Time service analysis
Use cases