One Does Not Simply Put Machine Learning into Production
Offered By: GOTO Conferences via YouTube
Course Description
Overview
Explore the challenges and considerations of implementing machine learning in production environments in this insightful conference talk from GOTO Copenhagen 2017. Delve into the important dimensions of accuracy, cost, maintainability, and interpretability, and understand the trade-offs between them. Learn about the technical challenges that arise when infusing existing products with machine learning capabilities or building ML-first products. Gain valuable insights from Henrik Brink, author of "Real-World Machine Learning," as he shares his expertise on successfully integrating machine learning into production systems. Discover practical strategies and best practices for overcoming obstacles and maximizing the potential of machine learning in real-world applications.
Syllabus
One does not simply put Machine Learning into Production • Henrik Brink • GOTO 2017
Taught by
GOTO Conferences
Related Courses
Computational NeuroscienceUniversity of Washington via Coursera Reinforcement Learning
Brown University via Udacity Reinforcement Learning
Indian Institute of Technology Madras via Swayam FA17: Machine Learning
Georgia Institute of Technology via edX Introduction to Reinforcement Learning
Higher School of Economics via Coursera