V V Srimannarayana Reddy Tetali·Nov 2How Naive Bayes Actually Works: Understanding the Algorithm Behind the PredictionsIntroduction to Naive Bayes
Deepak Mehta·Oct 24Broad Categories of Machine-Learning Models: Supervised Learning Models — Part dArticle 2d of 25 — Regression & Evaluation MetricsA response icon1A response icon1
Nivedita Bhadra·Sep 21Revise ML Algorithms for an InterviewA practical refresher on the machine-learning algorithms I want to understand before walking into an interview
InILLUMINATIONbyMedisumeet·Sep 10Linear Regression in Two MinutesHi technocrat! In this blog, I’m going to explain linear regression in the easiest way you’ve ever learned it.A response icon1A response icon1
Sudha Rani Maddala·Aug 6Python for Data Science — Your First Classification ModelIn the previous article, we built our first Regression Model and learned how machine learning can predict numerical values such as:A response icon1A response icon1
Pragathi Velu·Aug 3Logistic Regression — How AI Says Yes or NoSeries 3, Part 2: ML Algorithms, Simply Explained
Parvez Mohammed @ Techlatest.net·Jun 10Build an ML Model That Actually Ships: A 6-Step Visual WalkthroughMost people picture machine learning like this: pick an algorithm, call .fit(), done.
Ritu Raj·Jun 5Why Neighbors Matter: A Deep Dive into K-Nearest Neighbors (KNN)In real life, we often judge something based on its surroundings. If you move into a new neighborhood and see clean streets, friendly…
TechWealthBuzz·May 3scikit-learn: The Complete Practitioner’s Guide to Machine Learning in PythonFrom raw data to production-ready models — everything you actually need to know
