Sonia Akther·1d agoHow to Build a Python Evaluation Pipeline for AI ModelsTurn model testing into a repeatable system that measures quality, latency, cost, failures, and regressions before release.A response icon1A response icon1
InAgents Under TestbyAsad Khan·4d agoRed-Teaming ≠ Agent Assurance: Cisco AI Defense + Splunk: What They Check, What’s MissingCisco got into agent evaluation this year in actually two ways: via AI Defense and via Splunk (which they own).
Thang Tran·4d agoMLOps Core: Sizing Datasets and Choosing Open-Source Frameworks for RAG Fine-TuningThis post is for considering frameworks to generate datasets and evaluate the quality of RAG and fine-tuning for local LLM inference.
Diogo Ribeiro·5d agoA Label Is Not an EventI rebuilt the published baseline on an open dataset of in-home dementia monitoring, reproduced its 80% sensitivity, and then asked what the…
UNICEF Innovation Insights·5d agoFive hard questions innovation teams need to answer (honestly) before scalingBy Shalini Subbiah, Monitoring and Evaluation Specialist, UNICEF Office of InnovationA response icon1A response icon1
Faramarz Kowsari·6d agoYour Machine Learning Model Is 99% Accurate. But Can You Trust It?Why model evaluation may be the most underestimated skill in artificial intelligence — and how 104 handwritten visual lessons can change…
Brolly Ai·Nov 7ML Model Evaluation: Accuracy, Precision and Recall in Simple WordsImagine you build a spam filter for emails. You test it, and it shows 95 percent accuracy. Sounds great, right? You are ready to celebrate…
InLevel Up CodingbyKasrasadatsharifi·Nov 6Vision Transformers Part1: Why Replace Convolution with AttentionUnderstanding vision transformers foundation, architectural differences and performance comparisons with CNNs. Some of the graphs in this…A response icon1A response icon1
Christos Adam Lee·Nov 5Why a 95 Percent AI Score Can Still Be MisleadingA fictional support-ticket experiment shows what a high accuracy score leaves out.
Rupali Gauravaram·Nov 4Don’t trust a model’s accuracy alone: precision, recall and specificity explainedI’ve mixed up the different machine learning metrics while explaining them on more than one occasion. I found that quickly drawing a…
