(1/2) I am excited to present at the useR!2024 conference on July 2nd!
I am going to run a virtual workshop about deployment and monitoring data and ML pipelines using free and open-source tools. This includes setting pipelines using GitHub Actions, Docker 🐳, R, and Quarto 🚀.
The MLX is Apple's framework for machine learning applications on Apple silicon. The MLX examples repository provides a set of examples for using the MLX framework. This includes examples of:
✅ Text models such as transformer, Llama, Mistral, and Phi-2 models
✅ Image models such as Stable Diffusion
✅ Audio and speech recognition with OpenAI's Whisper
✅ Support for some Hugging Face models
@ramikrispin@BenjaminHan How do this and corenet (https://github.com/apple/corenet) fit together? The corenet repo has examples for inference with MLX for models trained with corenet; is that it, does MLX not have, e.g., activation and loss fns, optimizers, etc.?
@Lobrien@BenjaminHan The corenet is deep learning application where the MLX is array framework for high performance on Apple silicon. This mean that if you are using mac with M1-3 CPU it should perform better when using MLX on the backend (did not test it myself)
A former US military intelligence official released a letter on Monday that explained to his colleagues at the Defense Intelligence Agency (DIA) that his November resignation was in fact due to “moral injury” stemming from US support for Israel’s war in Gaza and the harm caused to Palestinians.
Harrison Mann, an army major, would be the first known DIA official to quit over US support to Israel.
Man said he felt shame and guilt for helping advance US policy that he said contributed to the mass killing of Palestinians.
“At some point, whatever the justification, you’re either advancing a policy that enables the mass starvation of children, or you’re not,” Mann wrote.
Version 0.12.0 of the skforecast Python library for time series forecasting with regression models was released this week. The release includes new features, updates for existing ones, and bug fixes. 🧵👇🏼
(2/2) Here are some of the new features:
✅ Ability to forecast multiple series with different lengths and/or different exogenous variables per series.
✅ Bayesian hyperparameter search is now available for all multiseries forecasters using optuna as the search engine.
✅ New forecasting models based on deep learning models (RNN and LSTM)
✅ New methods for creating prediction intervals
On June 15th, my colleague Mónica and I from @EA SEED will be presenting some of our work on #MachineLearning tools for #GameAudio at #AESEurope in Madrid. Really looking forward to visiting UPM again!
Looking for better data splits for #machinelearning? Look no further than astartes, a #pyOpenSci package from Jackson Burns, Kevin Spiekermann, and himaghna!
astartes is an #openscience, #opensource#Python package that implements many similarity- and distance-based algorithms to partition data into more challenging splits. Separate from astartes, you can use these splits to better assess out-of-sample performance with any ML model of choice.
Wie wird #KI & #MachineLearning die Software-Entwicklung beeinflussen? Diskutiert mit bei der uphillconf 2024, die wir als Bronzesponsor unterstützen. Es sind nur noch wenige Workshop-Tickets verfügbar! https://www.uphillconf.com/
Vraiment cool la série #Machine sur @arte 🔥
Un mélange explosif entre kungfu et lutte des classes avec Margot Bancilhon et la participation improbable de Joey Starr
Franchement à voir
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
We’re so excited to announce the support of survival analysis for time-to-event data across tidymodels!
• The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles.
• Survival analysis is now a first-class citizen in tidymodels, giving censored regression modeling the same flexibility and ease as classification or regression.
@stefan Wait. I only get to see one at the time?! I mean, I build one, and then it show the machine working without any neighbours... How come there's neighbours in this video?
If you had the feeling that the online discussion about COVID-19 vaccines was biased depending on the actors, you are right.
Using #MachineLearning and #NetworkScience we have shown that being a human or a bot, verified or unverified (according to previous Twitter rules) and political leaning were relevant factors for choosing the words in posts and, accordingly, the corresponding emotions to trigger.
A genuine computational social science study, led by Anna Bertani for her Msc thesis, now published also in collaboration with Riccardo Gallotti and Pierluigi Sacco
the ask envision on the @letsenvision app is cool, I loaded a 50 page pdf and it just do a RAG on it and answers my questions comprehensively, people should use it more, I hope in future I can load entire folders of document on desktop to do rag #machineLearning#AI#blind#disability
Calling all data enthusiasts: ever heard of Orange (https://orangedatamining.com/)? Recently stumbled upon this tool for data mining and machine learning. It's Python-based and completely open-source. Sounds pretty good to me? Any users here?
