Managing (4) - ML Teams - Full Stack Deep Learning скачать в хорошем качестве

Managing (4) - ML Teams - Full Stack Deep Learning

New course announcement ✨ We're teaching an in-person LLM bootcamp in the SF Bay Area on November 14, 2023. Come join us if you want to see the most up-to-date materials building LLM-powered products and learn in a hands-on environment. https://www.scale.bythebay.io/llm-wor... Hope to see some of you there! --------------------------------------------------------------------------------------------- How to manage machine learning projects properly? More videos at https://course.fullstackdeeplearning.com Summary Manage Machine Learning projects can be very challenging: In Machine Learning, it is hard to tell in advance what’s hard and what’s easy. Machine Learning progress is nonlinear. There are cultural gaps between research and engineering because of different values, backgrounds, goals, and norms. Often, leadership just does not understand it. The secret sauce is to plan the Machine Learning project probabilistically! Attempt a portfolio of approaches. Measure progress based on inputs, not results. Have researchers and engineers work together. Get end-to-end pipelines together quickly to demonstrate quick wins. Educate leadership on Machine Learning timeline uncertainty.