Jeevani·2d agoNaive Bayes Algorithm: Understanding the Power of Probability in Machine LearningIntroduction
Waheedkhan·2d agoBuilding My First ML Model: Student Marks Prediction Using Python and Random Forest RegressionFrom raw student data to training, evaluating, and making predictions with a Machine Learning model.
Mysalashravani·Nov 5Machine Learning Workflow & Data PreprocessingA practical guide to the end-to-end ML pipeline, preparing data, training models, evaluating performance, and avoiding data leakage.
Sarbani·Nov 2Balancing Bias and Variance: The Key to Better ML ModelsIn machine learning, bias and variance are two sources of prediction error. They describe two different aspects of a model’s predictions…A response icon1A response icon1
InNeurologic AIbyHimanshu Kale·Oct 28We Ran Out of GPU Memory on One Very Long Sentence. Here’s How We Fixed ItHey folks! Over the past few weeks we’ve been trying to train a model on very long texts, and we kept running into one stubborn wall: “the…
InPython in Plain EnglishbyNicolas Rowan·Oct 196 Ways to Handle Missing Data — and Only 2 Improved the ModelFilling every blank is easy. Working out whether it helped the model takes more effort.
Swanandiug·Oct 10Black Box to XAI : A story of LIME, SHAP, GRAD- CAM and a curvy graph of ROCDavid Heinemeier Hansson, the creator of the RAILS framework, alleged that Apple Pay allocated him 20x higher credit than his wife, even…
Osvaldo Rios Zambrano·Oct 9A 140M-parameter model on CPU vs.How a small encoder, trained by distillation, decided ~20× faster than a general-purpose engine and played at expert level, and the three…
Kenan Ayvataş·Oct 6400,000 Replays: The Smallest Case in Anthropic’s Report Is the One About YouNext to 151 million, the number 400,000 looks like a rounding error.
