Enterprises using multiple AI models are underestimating failure rates by 2.25x

A study of 67 AI models finds enterprises underestimate multi-model failure rates by 2.25x, and offers a free test to check routing infrastructure first.
IEEE

Comparative Analysis of State of Charge Estimation Methods for Li-Ion Batteries Using Kalman Filter Variants and Machine Learning Techniques for Electric Vehicle Applications

Abstract: State of Charge (SoC) measurement accuracy stands as a fundamental requirement to boost both safety and power performance together with energy efficiency in Battery Management Systems (BMS) ...
marktechpost

Darts: A New Python Library for User-Friendly Forecasting and Anomaly Detection on Time Series

Time series data, representing observations recorded sequentially over time, permeate various aspects of nature and business, from weather patterns and heartbeats to stock prices and production ...
TheServerSide

Shorter code, fewer bugs: Python's syntax is its saving grace

A few months ago, I had a discussion with some friends online. The premise of the discussion was that even if you account for complexity, shorter code is more likely to be bug-free code. As a C ...
GitHub

Image Preprocessing and Comparison Library

1. Global Metrics - Peak Signal-to-Noise Ratio (PSNR) - Root Mean Square Error (RMSE) - Normalized Cross-Correlation (NCC) - Correlation Coefficient - Mean Absolute ...
GitHub

Machine Learning with LightGBM and Python

What is this book about? Machine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems ...