Yesterday I gave a lecture at @Stanford
's CS25 class on Transformers! The lecture was on how “emergent abilities” are unlocked by scaling up language models. Emergence is one of the most exciting phenomena in large LMs… Slides:
MACHINE LEARNING
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Emergent Abilities in Language Models Through Scaling
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Data2vec 2.0: 16x Faster Self-Supervised Learning Across Modalities
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Data2vec 2.0 can train self-supervised speech, vision & text models up to 16x faster than the most popular existing algorithm for images — achieving the same accuracy. Read more & get the open source code https://
bit.ly/3H9mPf7 -
Essential Math Topics for Machine Learning Success
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2/I’ve often said “don’t worry about it” when it comes to math, because math shouldn’t hold anyone back from making progress in ML. And, understanding some key topics in linear algebra, calculus, and prob & stats will help you better get learning algorithms to work.
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Math for Machine Learning and Data Science Course Launches on Coursera
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1/Math for Machine Learning and Data Science is now available on Coursera! Taught by @luis_likes_math
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Batchnorm as a Challenging Interview Question for Candidates
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For a while I thought an excellent interview question would be to ask the candidate about batchnorm and measure the amount to which their face contorts
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As the Years Go By: Workplace Evolution in Tech
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As the years go by… (comic v/
@_workchronicles
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Open-source ML Tools Content Series Coming Soon
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That's it. Hope you enjoyed reading this. I will be sharing more content on all open-source ML Tools in the coming threads. Follow me @Sumanth_077 so won't miss what's coming next.
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Bento ML: Open Source Framework for Production ML Models
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7. Bento ML It is an open source model serving framework that helps you take your ML Models to Production https://
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ZenML: Open-Source ML Pipeline Framework Integration Tool
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5. ZenML Open-source pipeline framework that integrates all your ML tools https://
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Deepchecks: Python Package for ML Model and Data Validation
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4. Deepchecks Deep checks is a Python package for comprehensively validating your machine learning models and data with minimal effort. https://
github.com/deepchecks/dee
pchecks
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