Machine Learning

ramikrispin,
@ramikrispin@mstdn.social avatar

(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 🚀.

When 📆: July 2nd at 10 AM PST

#Rstats #MachineLearning #DataScience #MLops

ramikrispin,
@ramikrispin@mstdn.social avatar

(2/2) The event is virtual and open. More details and to register in the link below (search for the event) 👇🏼

https://events.linuxfoundation.org/user/program/virtual-schedule/

Thanks to the conference organizers for the invite!

dustcircle,
@dustcircle@masto.ai avatar
ramikrispin,
@ramikrispin@mstdn.social avatar

MLX Examples 🚀

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

🔗 https://github.com/ml-explore/mlx-examples

Lobrien,

@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.?

ramikrispin,
@ramikrispin@mstdn.social avatar

@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)

collabora,
@collabora@floss.social avatar

Just a few days to go before #IOTSWC24 kicks off in Barcelona! Join us with STMicroelectronics as we showcase #MachineLearning video analytics with #GStreamer on the STM32MP2! http://col.la/iot24 #STPartnerProgram #STAuthorizedPartner

MMRnmd, French
@MMRnmd@todon.eu avatar

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.

#GazaGenocide #USArmy #DIA #Intelligence ##HarrisonMann

https://www.theguardian.com/us-news/article/2024/may/13/military-resignation-gaza-war

ramikrispin,
@ramikrispin@mstdn.social avatar

(1/2) New release for skforecast 🎉

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. 🧵👇🏼

#timeseries #forecasting #machinelearning #deeplearning #python

image/png
image/png

ramikrispin,
@ramikrispin@mstdn.social avatar

(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

Code 🔗: https://github.com/JoaquinAmatRodrigo/skforecast
Release notes 🔗: https://skforecast.org/0.12.0/releases/releases

JGarciaMartin,

On June 15th, my colleague Mónica and I from
@EA SEED will be presenting some of our work on tools for at in Madrid. Really looking forward to visiting UPM again!

https://aeseurope2024.sched.com/event/1dQtK/incorporating-a-machine-learning-research-project-into-game-audio-production-the-exflowsions-case-study

pyOpenSci,
@pyOpenSci@fosstodon.org avatar

Looking for better data splits for ? Look no further than astartes, a package from Jackson Burns, Kevin Spiekermann, and himaghna!

astartes is an , 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.

📄 Docs: https://jacksonburns.github.io/astartes/

jakmarcin,
@jakmarcin@mstdn.science avatar

I am looking for a post-doc to work with me on application for thermonuclear fusion plasmas. We want to use generative AI models to fill the gaps in existing image datasets and to help able to improve real-time control mechanisms. Sounds exciting? Apply! https://www.ipp.mpg.de/job-49bb2918863ec0a96b217258beca4dcf

hostpoint, German
@hostpoint@swiss.social avatar

Wie wird & 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/

homlett,

’: The AI directing ’s bombing spree in
https://www.972mag.com/lavender-ai-israeli-army-gaza/
“The result, as the sources testified, is that thousands of — most of them women and children or who were not involved in the fighting — were wiped out by Israeli airstrikes, especially during the first weeks of the war, because of the ’s decisions.”

skiserv, French
@skiserv@pouet.chapril.org avatar

Vraiment cool la série sur @arte 🔥
Un mélange explosif entre kungfu et lutte des classes avec Margot Bancilhon et la participation improbable de Joey Starr
Franchement à voir

dispo jusqu'au 18 mai - 6 épisodes
https://www.arte.tv/fr/videos/RC-025010/machine/

dom,
@dom@vis.social avatar
alvinashcraft,
@alvinashcraft@hachyderm.io avatar
tedunderwoodillinois,

30 billion words of audio transcriptions from 30 million YouTube videos, in multiple languages. More modalities coming soon. From Pleias. https://huggingface.co/datasets/PleIAs/YouTube-Commons

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