Neural Nets for NLP – Carnegie Mellon This is a great course that covers neural networks techniques and algorithms for natural language processing. Covers neural network architectures for language modelling such as recurrent networks and transformers, tips and tricks for
@jeande_d
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State of GPT: Karpathy Explains LLM Training Paradigms at Microsoft Build
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State of GPT – Andrej Karpathy at Microsoft Build Such awesome talk on state of GPT and other LLMs. Karpathy in his usual best teaching style talks about the training paradigms of large language models(pretraining, supervised finetuning, reward modelling, RLHF), prompting
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Gratitude to Content Creators Supporting AI Community Growth
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Reaching this number would not have been possible without the support of other fav and fantastic content creators: @DrJimFan
, @arankomatsuzaki
, @AlphaSignalAI
, @tunguz
, @rasbt
, @svpino
, @omarsar0
, among others. In Jim words, "you keep us grounded in the overwhelming tide of AI". -
Reaching 30K Followers: Gratitude and Future AI Content Plans
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30K followers It's wild to see our little learning community reaching this milestone. Thank you for being part of it. I will keep to share ideas and resources that I find useful and sometime, long-form content around select topics in AI. The best is yet to come.
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Deep Generative Models Stanford CS236 Course Notes
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Deep Generative Models – Stanford CS236 Notes Excellent notes on deep generative models. Covers different types of generative networks: autoregressive models, VAE, normalizing flow models, GANs. https://
deepgenerativemodels.github.io/notes/ -
Recommended Introductory Machine Learning and Deep Learning Courses
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It could be beneficial if you have taken an introductory course to machine learning/deep learning before. Some few suggestions(pick one of them): – Neural Networks: Zero to Hero: https://
karpathy.ai/zero-to-hero.h
tml
…
– CS229 Machine Learning: https://
youtube.com/playlist?list=
PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
…
– Intro to Deep Learning -
Stanford CS25 Transformers United V2 Course Overview
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Stanford CS25 Transformers United V2 Two years ago, a group of instructors at Stanford introduced a dedicated course about transformers, the engine of recent advances in AI. The course lectures covers introduction to transformers, how they work, different kind of transformers
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Prompt Engineering Guide: LLM History, Strategies and Safety
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Prompt Engineering Guide A great repository that covers history of LLMs, strategies, guidelines, and safety recommendations for working with and building programmatic systems with LLMs. https://
github.com/brexhq/prompt-
engineering
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Cohere Releases Comprehensive LLM University Curriculum
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LLM University – Cohere Cohere just released a comprehensive LLM curriculum. The curriculum covers basic NLP foundations and advanced topics like large language models(LLMs). Coming from a company building NLP & LLMs tools for developers and users, this LLM curriculum is as
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Comprehensive Practical Guide to Large Language Models Resources
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A well-curated list of practical resources of large language models(LLMs). Contains LLMs evolutionary tree, example models, and papers. This is a handy resource for practitioners that want to dive deep into LLMs. Repo: https://
github.com/Mooler0410/LLM
sPracticalGuide
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Related paper: