Overview
Explore applied machine learning for startups in this 32-minute conference talk by Arshak Navruzyan. Gain insights into training qualified practitioners, the importance of pairing quantitative experts with software engineers, and the progress of fellowship programs. Learn about delivering real results, essential ML guidelines, and crucial model characteristics. Discover Jeremy Howard's cheatsheet, transfer learning techniques, vector representation of words, and the state-of-the-art in Natural Language Processing. Understand the application of RNN with word embedding and the process of selecting partners in the ML startup ecosystem.
Syllabus
Intro
Machine Learning at Startups
Training Qualified Practitioners
Quant + Software Engineer Pair
Fellowship Progress
Delivering Real Results
ML Basic Guidelines
Important Model Characteristics
Jeremy Howard Cheatsheet
Transfer Learning
Vector Representation of Words
Natural Language Processing SOTA
RNN with Word Embedding
Select Partners
Taught by
Launchpad