A major release to Ollama - version 0.1.32 is out. The new version includes:
β Improvement of the GPU utilization and memory management to increase performance and reduce error rate
β Increase performance on Mac by scheduling large models between GPU and CPU
β Introduce native AI support in Supabase edge functions
Interpreting the LHC collisions is extremely data-intensive, and #CMSPaper 1282 describes how modern software techniques so our software (and #machinelearning) can run on many different platforms/processors and still efficiently and transparently reconstruct our collisions https://arxiv.org/abs/2402.15366
This week, PyMC version v5.13.0 was released. PyMC is one of the main #Python π libraries for πππ²ππ¬π’ππ§ statistics β€οΈ. It provides a framework for probabilistic programming, enabling users to build #Bayesian models with a simple Python API and fit them using πππ«π€π¨π― ππ‘ππ’π§ ππ¨π§ππ πππ«π₯π¨ (MCMC) methods π.
The new release includes new features, bug fixes π, and documentation improvements π. More details on the release notes π π #DataScience#machinelearning#statistics
(1/2) Models Demystified - A Practical Guide from t-tests to Deep Learning πππΌ
The Models Demystified is a new book by Michael Clark and Seth Berry that focuses on the mechanizing of core data science algorithms. That includes the following topics:
β Linear and logistic regression
β Generalized Linear Models
β Regularization methods
β Model training approaches
β Deep learning and neural networks
β Causal Modeling
Whenever I see OpenAI's Sam Altman with his pseudo-innocent glance, he always reminds me of Carter Burke from Aliens (1986), who deceived the entire spaceship crew in favor of his corporation, with the aim of getting rich by weaponizing a newly discovered intelligent lifeform.
Weβre so excited to announce the support of survival analysis for time-to-event data across tidymodels!
β’ The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles.
β’ Survival analysis is now a first-class citizen in tidymodels, giving censored regression modeling the same flexibility and ease as classification or regression.
Andrej Karpathy just released a new repo with an implementation of training LLM with pure C/Cude with a few lines of code π. This repo, according to Andrej Karpathy, is still WIP, and the first working example is of GPT-2 (or the grand-daddy of LLMS π ) ππΌ
I don't have a GPU that'll run it, so I have no idea what it's like, but it deserves more attention for the effort. Boost for visibility if that's your thing?