#machinelearnig — Public Fediverse posts

🤖 Smarter Together: RPA Meets AI for Unmatched Efficiency

RPA and AI are revolutionizing business processes through intelligent automation and real-time decision-making.
🚀 Boost productivity, reduce errors, and embrace the future of automation.

📖 Dive deeper—read the full blog to explore real-world impact! 👉

https://neuronus.net/en/blog/robotic-process-automation-and-ai

#RPA #AI #RoboticsProcessAutomation #ArtificialIntelligence #CollaborationOfRPAandAI #MachineLearnig #BusinessGrowth #Neuronus

This article by Kamil Rzechowski explains how to set up and use a dev container extension for VSCode 💡

#ml #machinelearnig #ReasonFieldLab

https://softwaremill.com/dev-containers-in-machine-learning/

Has anyone got references (or ideas/recommendations) for how to perform #data #augmentation on #scrnaseq data (to use in training #ann)?

This is the only paper I could find, but maybe I am not searching for the right thing...

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592700/

#machinelearnig #biology

The TargetEncoder PR has been merged into the scikit-learn main branch!

https://github.com/scikit-learn/scikit-learn/pull/25334

It's a very efficient way to deal with high cardinality categorical variables for supervised machine learning tasks. See the following quick tutorial to compare its performance with one-hot encoding, ordinal encoding and native support of categorical variables in Gradient Boosted Trees:

https://scikit-learn.org/dev/auto_examples/preprocessing/plot_target_encoder.html

It will be part of scikit-learn 1.3.

#sklearn #PyData #SciPy #MachineLearnig #Python

I'm working on a free YouTube end-to-end course to simplify working with #OpenAI for both seasoned and new software engineers.

Stay tuned!

#chatgpt #blazor #dotnet #csharp #openai #artificialgeneralintelligence #machinelearnig

I'm starting to feel more and more convinced of the usefulness of model pretrained on a classification task on ImageNet, especially beyond a certain accuracy #machinelearnig #computervison

This article really raises the question how much of the #tech boom of the last decade, including #machinelearnig and #DataScience, was real innovation and how much was just taking advantage of low interest rates and investors having nowhere else to go with their money? https://www.nytimes.com/2023/01/23/technology/tech-interest-rates-layoffs.html

Reminder that #MachineLearnig is only as smart as its dataset, and dumping massive amounts of bogus data into it WILL directly effect its performance, reliability and accuracy.