An overview of what tokens and embeddings mean in the context of LLMs - and related models
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MLX 20/80. With 20% effort, hope to get 80% covered on MLX's offerings. And, I don't stand by this claim.
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Probably definitely incomplete notes on probability.
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Chapter-wise notes for Deep Learning with Python with Python and Clojure code samples. The book is not done. These notes are evolving as I get deeper both into the book and the accompanying code.
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For polyglots who can't keep too many languages in their heads and need a deep refresher.
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Summarized guide for features I commonly use, for quick reference.
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Clojure Notes - An aimless dump of anything and everything interesting I find and manage to record.
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