Learning

Preparing Video Data for Deep Learning: Introducing Vid Prepper

to preparing videos for machine learning/deep learning. As a consequence of the scale and computational cost of video data, it's vital that it's processed in as efficient a way possible to your use...

Learning Triton One Kernel At a Time: Vector Addition

, slightly optimisation goes a great distance. Models like GPT4 cost greater than $100 tens of millions to coach, which makes a 1% efficiency gain price. A robust strategy to optimise the efficiency of...

A Focused Approach to Learning SQL

Data is all over the place, but how do you draw insights from it? Often, structured data is stored in , meaning collections of related tables of knowledge. For example, an organization might store...

Fighting Back Against Attacks in Federated Learning 

Federated Learning (FL) is we train AI models. As an alternative of sending all of your sensitive data to a central location, FL keeps the information where it's, and only shares model updates....

AI and machine learning for engineering design

Artificial intelligence optimization offers a bunch of advantages for mechanical engineers, including...

The Machine Learning Lessons I’ve Learned This Month

in machine learning are the identical. Coding, waiting for results, interpreting them, returning back to coding. Plus, some intermediate presentations of 1’s progress. But, things mostly being the identical doesn't mean that there’s nothing...

Simpler models can outperform deep learning at climate prediction

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions...

Designing Trustworthy ML Models: Alan & Aida Discover Monotonicity in Machine Learning

Machine learning models are powerful, but sometimes they produce predictions that break human intuition. Imagine this: you’re predicting house prices. A 2,000 sq. ft. house is predicted cheaper than a 1,500 sq. ft. home. Sounds...

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