This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...

Why write ten lines of code when one will do? From magic variable swaps to high-speed data counting, these Python snippets will transform your code.

Overview: Structured online platforms provide clear, step-by-step learning paths for beginners.Real progress in data science comes from hands-on projects and co ...

Overview Pandas continues to be a core Python skill in 2026, powering data analysis, cleaning, and engineering workflows ...

Finding the right book can make a big difference, especially when you’re just starting out or trying to get better. We’ve ...

This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box.

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Abstract: Machine learning is widely used to solve networking challenges, ranging from traffic classification and anomaly detection to network configuration. However, machine learning also requires ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

ageml allows age modelling with a set of simple-to-use CLIs that produce comprehensive figures of the modelling steps and detailed logs for exploring the effectiveness of the trained models.