Natural Language Processing with Transformers: http://
amzn.to/4e4ZtHv
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Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question-answering.
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#NLProc #MachineLearning #AI #DeepLearning #DataScience
LLMS
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Natural Language Processing with Transformers: Build and Optimize NLP Models
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Mastering NLP: From Foundations to LLMs with Python
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Mastering #NLProc from Foundations to #LLMs — Apply Advanced NLP Techniques to Solve Real Business Problems using #Python: http://
amzn.to/3TawZDK by @lior_gazit & Meysam Ghaffari
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#DataScience #GenerativeAI #AI #MachineLearning #DeepLearning #GenAI #ML #DataScientist -
Test-time search drives ARC-AGI performance, not vision
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In general: there is a strong correlation between adding test-time search (or test-time training) to your model and ARC-AGI performance. There is zero correlation between adding vision as a modality and better performance. It's all about better reasoning, not at all about vision.
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Inverse correlation between task length and model performance explained
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Yes, there is an inverse correlation between task length and model performance — because model reasoning abilities decrease dramatically with context size, as has been demonstrated in many different domains with sequence-only data.
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ARC-AGI relies on symbolic reasoning, not visual perception
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If ARC-AGI required visual perception, you'd see VLMs outperform strict LLMs — by a lot. Everyone tried VLMs during the 2024 competition — no one got better results. Every single top entry used a strict LLM. As we've said many times: ARC-AGI is a 2D symbolic reasoning
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The Tensor Cookbook: Essential Resource for Machine Learning
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The Tensor Cookbook https://
bit.ly/3zx8UQx
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
o1-preview shows promise for medical reasoning and healthcare integration
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promising results of o1-preview for medical reasoning (though still lots of work to figure out how to integrate with the healthcare system)
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Author Notices ChatGPT Echoes Writing Habits from 2014 Book
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Haha fun fact: I used to”delve” 2x in my 2014 Python Machine Learning book 10 years as well. ChatGPT must have learned that habit from my older books