Data scientists should be more end-to-end | Machine Learning Monthly September 2020 скачать в хорошем качестве

Data scientists should be more end-to-end | Machine Learning Monthly September 2020

Every month I review the latest and greatest resources in the world of machine learning in a newsletter called Machine Learning Monthly. This is the video version of that newsletter for September 2020. And as usual, it's been a massive month on tour. Read the blog post - https://zerotomastery.io/blog/machine... Learn ML (beginner-friendly course) - https://dbourke.link/mlcourse Updates on my work - https://dbourke.link/newsletter Timestamps: 0:00 - Intro and hello 0:57 - How I'd start learning ML again video 1:47 - Shivan's project to analyze my YouTube data 4:16 - Free advanced NLP with spaCy course 5:43 - Explosion AI (one of my favourite AI companies) 6:15 - Text classification with TFIDF vs Word2Vec vs BERT 7:16 - TFIDF formula 8:35 - Super efficient on-device NLP 11:10 - Story of working on a NLP ML project 13:07 - Machine Learning from Scratch book by Danny Friedman 15:33 - 42 day project framework 16:05 - Learning Math for Machine Learning 17:35 - One of my favourite quotes on learning 19:06 - Four great questions for any ML project 19:48 - Data scientists should be more end-to-end 22:43 - Story of being held back on a project 25:34 - GitHub Actions for MLOps & Data Science 27:15 - Microsoft DeepSpeed framework for faster and more efficient model training 30:32 - Roboflow's Ultimate Guide to Object Detection in 2020 33:37 - Using AI and computer vision for agriculture 36:25 - My favourite resource for the month 37:00 - Outro Support on Patreon - https://bit.ly/mrdbourkepatreon Connect elsewhere: Web - https://dbourke.link/web Quora - https://dbourke.link/quora Medium - https://dbourke.link/medium Twitter - https://dbourke.link/twitter LinkedIn - https://dbourke.link/linkedin