NLP nerd @NLP_nerd
Willing to create a twitter account on NLP | Lead ML Scientist at https://t.co/82XnGhBNJu | Host of https://t.co/Pu94mhyB9s Joined February 2020-
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The Generative AI Divide: Why AI Demos Impress but AI Products Disappoint open.substack.com/pub/mindfulmac… #AI #LLMs #GenerativeAI
I'll be giving a talk about DataMapPlot at SciPy this year. Learn how to make the most of your data maps. cfp.scipy.org/scipy2025/talk…
We've fallen into a linguistic trap saying AI models "understand" and "reason." This anthropomorphizing is dangerous—we overestimate their flexibility while missing their actual superpowers: processing vast information and spotting patterns humans can't. bit.ly/43Tktws
Why I Never Skip Data Visualization (Even When Automating Everything) youtu.be/wHg08K67VQQ?si…
Thinking beyond Transformers | Learning from Machine Learning featuring @maximelabonne youtu.be/IOC2k5k8oto?si… Key learnings: -Transformers aren't the end game -Data quality remains unsolved -UI design shapes AI interaction Real learning happens in production, not benchmarks
open.substack.com/pub/mindfulmac… We process physical reality, experience subjective consciousness, and actively shape cultural evolution. This interactive participation may be the key to understanding not just consciousness, but the future relationship between humans and AI
Listen to @_amankhan on Learning from Machine Learning: Aman Khan: @arizeai, Evaluating AI, Designing for Non-Determinism youtu.be/v0eTTn7ZPEc?si…
Sebastian Raschka has transformed how data scientists and ML engineers learn and build AI. Explore 13 key lessons he shared on mastering machine learning and responsibly advancing AI, in @NLP_nerd's latest article. towardsdatascience.com/learning-from-…
AI should not be limited by comparisons to human reasoning. Check out: Discourse on Darwin's Descent and the Diversity of Intelligence open.substack.com/pub/mindfulmac…
The (true) story of development and inspiration behind the "attention" operator, the one in "Attention is All you Need" that introduced the Transformer. From personal email correspondence with the author @DBahdanau ~2 years ago, published here and now (with permission) following…
🎙️New episode of Learning from Machine Learning with @leland_mcinnes is out now! Dive into the mind behind UMAP & HDBSCAN libraries. From decomposing black boxes to building better tools, discover why understanding data geometry matters. youtu.be/6sSOr2Yaq80?si…
Learning from Machine Learning Preview... Episode 10 coming soon! youtu.be/yfkJ8Lh6Rvg?si… via @YouTube
The single most important thing I have learned about software development over my career is that if you do not aggressively fight complexity, it will eat you alive.
Newest episode of Learning from Machine Learning features @vanpelt from @weights_biases on MLOps, Weights and Biases, Evaluation, Entrepreneurship and more. Watch now on youtu.be/ZOBKLKzI3xY?si…
New (2h13m 😅) lecture: "Let's build the GPT Tokenizer" Tokenizers are a completely separate stage of the LLM pipeline: they have their own training set, training algorithm (Byte Pair Encoding), and after training implement two functions: encode() from strings to tokens, and…
Michelle Gill: AI-Assisted Drug Discovery, NVIDIA, Biofoundation Models, Creating Applied Research Teams | Learning from Machine Learning #8 open.substack.com/pub/mindfulmac… #NVIDIA #ai #MachineLearning
How can AI be used to speed up drug discovery? Listen in to @nvidia's Michelle Gill @modernscientist discuss the cutting edge research and development of biofoundation models. youtu.be/uXAqVifiSTw?si…
Enjoy my favorite exchange with @_inesmontani on Natural Language Processing vs. Natural Language Understanding from Episode 7 of Learning from Machine Learning #AI #DataScience #NLP
This year, I spent 38 hours training 1,029 models on @weights_biases! My #longestrun is volcanic-elevator-817 - cdn.wandb.ai/year-wrapped-2…

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