Machine Learning Engineering by Andriy Burkov | Book Review

Machine Learning Engineering by Andriy Burkov | Book Review

Jan 19, 2021
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Every month I collect the most outstanding resources in the world of machine learning and put them together in a short report called Machine Learning Monthly. This video adds commentary to those resources. Jump to 21:25 for a review of the Machine Learning Engineering book by Andriy Burkov

0:00 - Intro/hello 1:29 - The 10 Commandments of Self-Taught Machine Learning Engineers 3:30 - Kevin's ML powered mask detecting Telegram Bot 6:50 - NLP fire sale (plethora of NLP resources) 7:25 - Modern Practical NLP by Johnathan Mugan 9:25 - Getting started with NLP by Elvis Saravia 10:35 - The Super Duper NLP repo (plenty of NLP examples) by Quantum Stat 12:30 - NLP News by Sebastian Ruder 14:00 - Phenomenal NLP repo by Tae-Hwan Jung 15:46 - State of AI Report 2020 16:40 - A 2020 guide to Data & Infrastructure 19:55 - Putting ML into production course by Made with ML 21:25 - My new favourite ML book: Machine Learning Engineering by Andriy Burkov 23:12 - The NumPy manifesto 25:18 - The Incredible PyTorch (bulk PyTorch examples) by Ritchie Ng 26:35 - Transformers for computer vision 30:15 - Training a custom object detection model for mobile guide by Jim Su from Roboflow 32:25 - Gradient Dissent podcast by Weights & Biases 34:00 - Summary/goodbye 👋
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