torch v0.11.0 is now on CRAN. This release features much-enhanced support for executing JIT operations. We also amended loading of model parameters, and added a few quality-of-life improvements, like support for temporarily modifying the default torch device, support for specifying data types as strings, and many more.
We were joined by Joris Van den Bossche talked about the work being done with Pandas. Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
In this episode of Open Source Directions, we were joined by Thomas Wiecki once again who talked about the work being done with PyMC. PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.
In this episode of Open Source Directions we were joined by Matthew Seal who talked about the work he has been doing with Jupyter and Nteract. Matthew also discussed a particular topic: common Jupyter tools and their adoption for various use cases in the wild.
This article discusses GPT-2 and BERT models, as well using knowledge distillation to create highly accurate models with fewer parameters than their teachers
In this episode, we have an engaging and very entertaining discussion with Jono Bacon, the founder of Jono Bacon Consulting. Jono was Director of Community at notable companies such as Github, Canonical, and XPRIZE. He is one of the top (if not the top) experts in the world when it comes to building strong communities.
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