mlsquare
mlsquare is an open source, deep tech initiative to democratize ML. The fundamental tenet is, use ML to make ML useful.
Past ML software projects
WIP ML software projects
- FedEm: a framework to decentralize the development of LLMs
Upcoming ML software projects
neural tokenizers to enable the extension of English-centric LLMs to other languages
model grafting via analytical and numerical approximations to enable efficient cross-architecture transfer learning
compute & data efficient training via layer-by-layer and block-by-block LLM training, which is inherently embarrassingly parallel, and with potential analytical update rules (no need for backprop and gradients)
deep kernel machines a framework for composing many transformer-like architectures with specifiable inductive biases
xKANs a framework for composing many KAN-like architectures with specifiable non-parametric function approximators like cubic B-splines, Chebyshev polynomials, Wavelets, etc..
embeddings for tabular data bridge the gap between tabular and modern deep learning models, and make deep learning architectures perform no worse than tree-based models like the battle tested catboost
Upcoming Courses
MLOps: Theory and Practice for upper level undergraduate students
Theory of Deep Learning: Why it works - A Constructionist Approach for upper level undergraduate students
Ilya Sutskever’s 30 papers - Walk through
Yours openly
The Saddle Point
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