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  1. 14 de mai. de 2024 · Jeremy Howard (Fast.ai), Shreya Shankar (UC Berkeley), and Hamel Husain (Parlance Labs) join Hugo Bowne-Anderson to talk about how LLMs and OpenAI are changing the worlds of data science, machine learning, and machine learning engineering.

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  2. 6 de mai. de 2024 · Part 1 2022. arjanhada (Arjan hada) May 6, 2024, 5:08pm 1. How does Jeremy Howard generate table of contents in his kaggle notebooks ? vinayjose (Vinay Jose) May 7, 2024, 5:51am 2. In Kaggle, it is automatically created when a version of the notebook is saved. The TOC will not be visible in the edit mode tho.

  3. 22 de mai. de 2024 · Jeremy Howard is known for his contributions to deep learning and data science, co-founding the fast.ai educational initiative that democratizes access to cutting-edge AI learning. 1 hr. 20 MAY 2024. Bonus Episode: Sam Altman (CEO, OpenAI) Talks GPT-4o and Predicts the Future of AI.

    • Redpoint Ventures
  4. Há 3 dias · A Hackers' Guide to Language Models. Jeremy Howards new 1.5 hour YouTube introduction to language models looks like a really useful place to catch up if you’re an experienced Python programmer looking to start experimenting with LLMs.

  5. Há 3 dias · Getting Started With CUDA for Python Programmers if, like me, you’ve avoided CUDA programming (writing efficient code that runs on NVIGIA GPUs) in the past, Jeremy Howard has a new 1hr17m video tutorial that demystifies the basics.

  6. Há 3 dias · Mastering LLMs: A Conference For Developers & Data Scientists ( via) I’m speaking at this 5-week (maybe soon 6-week) long online conference about LLMs, presenting about “LLMs on the command line”. Other speakers include Jeremy Howard, Sophia Yang from Mistral, Wing Lian of Axolotl, Jason Liu of Instructor, Paige Bailey from ...

  7. Jeremy Howard: Co-Founder Answer.AI & Fast.AI. - Build Applications For LLMs in Python. Sophia Yang: Head of Developer Relations, Mistral AI. - Best Practices For Fine Tuning Mistral. Simon Willison: Creator of Datasette, co-creator of Django, PSF Board Member. - Language models on the command-line.