the most valuable skill in the world is systems engineering: the ability to debug, understand, and improve a complex system with limited/poor measurement THIS is what makes great scientists, engineers, PMs, operators, doctors & investors not truly taught in school outside STEM
EDUCATION
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STEMinism: Empowering Women in STEM and Technology
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What is STEMinism? https://
bit.ly/3DiKRmz #STEM #WomeninTech -
Stanford CS324 LLM Course: Comprehensive Notes on Large Language Models
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[Lecture notes] Stanford CS324 – Large Language Models Excellent notes on various topics related to large language models: fundamentals of language models, capabilities of LLMs, data behind LLMs, modeling, training, scaling laws, selective architectures, task adaptation, and
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Skills to Keep Pace with the Future of Work
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‘Change is the only certainty in tech’: Skills to keep pace with the #FutureofWork https://
bit.ly/45SYhmo via @siliconrepublic -
IBM TechXchange Premier Technical Learning Event with AI Track
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IBM TechXChange is the premier technical learning event designed with technologists for technologists. Register today and join us for the #AI track to learn about generative AI using #watsonx and more: https://
ibm.co/44iEyuh -
NVIDIA Interns Complete Summer Internships in AI Tech
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Our interns around the globe are wrapping up their summer internships, taking on real-world assignments to develop their careers, while having some fun along the way. #NVIDIAlife https://
blogs.nvidia.com/blog/2023/08/1
6/nvidia-life-interns-2023/?ncid=so-twit-331457
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Stanford HAI’s bipartisan push for public sector AI development
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@StanfordHAI ‘s bipartisan work in resourcing the public sector for developing AI for public good and for educating more students and young researchers across the nation
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Introduction book resource link shared
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There is also an introduction book: https://
probml.github.io/pml-book/book1
.html
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Free Foundational Machine Learning Course by Manaranjan Pradhan
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A free foundational course on machine learning by #ManaranjanPradhan. With 20 hours of recorded videos on YouTube, as well as numerous notebooks and exercises, it's useful for anyone looking to start learning about the basics of machine learning. https://
manaranjanp.com/docs/ML-Founda
tion
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NeurIPS 2023 LLM Efficiency Challenge and ULMFiT Recommendation
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The NeurIPS 2023 LLM efficiency challenge of course 🙂 https://
llm-efficiency-challenge.github.io Just recommend your Ulmfit paper with @seb_ruder to the students I am collaborating with the other day. Would be looking forward to the solutions you come up with for this one