Prompt Engineering for Outlier Detection
Learn how to detect outliers by doing a real-life data project and improve the process with AI.
Learn how to detect outliers by doing a real-life data project and improve the process with AI.
You can train, evaluate, and export a full ML pipeline in Python using TPOT with just a few lines of code.
Nebius Token Factory customers use distillation today for search ranking, grammar correction, summarization, chat quality improvement, code refinement, and dozens of other narrow tasks.
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In this article, we explore LOF through three simple steps: distances and neighbors, reachability distances, and the final LOF score. Using tiny datasets, we see how two anomalies can look obvious to us but completely different to different algorithms. This reveals the key idea of unsupervised learning: there is no single “true” outlier, only definitions. Understanding these definitions is the real skill. The post The Machine Learning “Advent Calendar” Day 9: LOF in Excel appeared first on Towards […]
Cashew Research uses AI to automate the market research process while still collecting real-world data from humans.
This week on StrictlyVC Download, Connie Loizos speaks with Science Corp. founder Max Hodak to discuss how brain-computer interfaces are arriving faster than anyone realizes. The Neuralink co-founder and former president shares how his company recently achieved what may be the biggest breakthrough in vision restoration in decades, enabling 80% of blind patients to read […]