The Beginner’s Guide to Machine Learning with Rust
Machine learning has become an essential tool for solving complex problems across various domains, from finance to healthcare.
A Gentle Introduction to Graph Neural Networks in Python
Graph neural networks (GNNs) can be pictured as a special class of neural network models where data are structured as graphs — both training data used to train the model and real-world data used for inference — rather than fixed-size vectors or grids like image, sequences, or instances of tabular data.
Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment
Training Diffusion Models with Reinforcement Learning We deployed 100 reinforcement learning (RL)-controlled cars into rush-hour highway traffic to smooth congestion and reduce fuel consumption for everyone. Our goal is to tackle “stop-and-go” waves, those frustrating slowdowns and speedups that usually have no clear cause but lead to congestion and significant energy waste. To train efficient …
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10 Must-Know Python Libraries for LLMs in 2025
Large language models (LLMs) are changing the way we think about AI.
Implementing Multilingual Translation with T5 and Transformers
This post is divided into three parts; they are: • Setting up the translation pipeline • Translation with alternatives • Quality estimation Text translation is a fundamental task in natural language processing, and it inspired the invention of the original transformer model.
Bias Detection in LLM Outputs: Statistical Approaches
Natural language processing models including the wide variety of contemporary large language models (LLMs) have become popular and useful in recent years as their application to a wide variety of problem domains have become increasingly capable, especially those related to text generation.
Understanding RAG Part VIII: Mitigating Hallucinations in RAG
Be sure to check out the previous articles in this series: •
6 Lesser-Known Scikit-Learn Features That Will Save You Time
For many people studying data science,
Debugging PyTorch Machine Learning Models: A Step-by-Step Guide
Debugging machine learning models entails inspecting, discovering, and fixing possible errors in the internal mechanisms of these models.
A Gentle Introduction to Transformers Library
The transformers library is a Python library that provides a unified interface for working with different transformer models.