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#classificationmodels

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MGMayank Goyalatp-winner-predictor-rf.hashnode.devJan 4 · 2 min read

From 59K ATP matches to a winner predictor (Random Forest)

I built an end-to-end machine learning classifier that predicts ATP tennis match winners using only pre‑match information. So the prediction is something you can realistically make before players step on court. GitHub Repo:- ATP-TENNIS Live demo...

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MAMbuotidem Awakmbuotidemawak.hashnode.devDec 13, 2025 · 6 min read

Explore Data Science in Fabric: A Beginner Friendly Guide

Data science can feel overwhelming when you are just starting out. There are many tools, new terms, and different roles involved. Microsoft Fabric was designed to reduce this complexity by bringing data science, data engineering, and analytics into o...

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UUplatzuplatz.hashnode.devOct 6, 2025 · 2 min read

🏷 AI Models Explained: Logistic Regression

📖 Logistic Regression may sound like Linear Regression, but it’s built for classification, not prediction. It helps AI decide between categories – spam vs not spam, churn vs stay, 1 vs 0. 1️⃣ The Foundations Works by applying a sigmoid (S-curve) f...

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DPDhairya Pateldhairya-ai-dev.hashnode.devAug 28, 2025 · 2 min read

Day 9 – Bayes’ Theorem & Naive Bayes Classifier

Hey everyone 👋 Dhairya here, Today’s focus was on one of the most fundamental ideas in probabilistic machine learning: Bayes’ Theorem and its practical use in the Naive Bayes classifier. 🔢 What I Learned Today 1. Bayes’ Theorem Formula: P(A∣B)=...

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PMPradeep Malagedl-confusion-matrix.hashnode.devJul 28, 2025 · 3 min read

Don't Be Confused by Confusion Matrix - Simple Words, Strong understanding

🤔 What is a Confusion Matrix? If you’ve just started learning Machine Learning, and you're hearing terms like True Positive, False Negative, and wondering what confusion matrix even means — this blog is for you. Let’s break it down in the most simpl...

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SRSathwik Reddymlmodels.hashnode.devApr 11, 2025 · 3 min read

Machine Learning Algorithms: Classification vs. Regression Models

Machine Learning (ML) is transforming industries across the globe by enabling systems to learn from data and make decisions without being explicitly programmed. At the heart of supervised learning lie two primary types of predictive modeling tasks: ...

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OKOmkar Kastureomkarkasture.hashnode.devOct 1, 2024 · 8 min read

Classification Models Part-2: Exploring LDA and KNN

Introduction In the first part, we explored what a classification model is, using logistic regression as an example, along with the confusion matrix and different performance evaluation methods. In this article, we'll dive into two additional classif...

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OKOmkar Kastureomkarkasture.hashnode.devSep 30, 2024 · 8 min read

Introduction to Classification Models: Exploring Logistic Regression

Introduction In this Article, we’ll be diving into three important classification models: Logistic Regression K-Nearest Neighbors (KNN) Linear Discriminant Analysis (LDA) As mentioned earlier, there are two types of prediction problems: Regress...

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RBRiya Boseblogbyriyabose.hashnode.devSep 25, 2024 · 8 min read

Mastering Classification Models: Advanced Techniques and Best Practices

Part - I https://blogbyriyabose.hashnode.dev/diving-deeper-into-machine-learning-a-detailed-exploration-of-regression-classification-and-clustering Part-II Classification models are essential tools in the machine learning arsenal, widely used across ...

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#classificationmodels

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From 59K ATP matches to a winner predictor (Random Forest)​

Explore Data Science in Fabric: A Beginner Friendly Guide

🏷 AI Models Explained: Logistic Regression

Day 9 – Bayes’ Theorem & Naive Bayes Classifier

Don't Be Confused by Confusion Matrix - Simple Words, Strong understanding

Machine Learning Algorithms: Classification vs. Regression Models

Classification Models Part-2: Exploring LDA and KNN

Introduction to Classification Models: Exploring Logistic Regression

Mastering Classification Models: Advanced Techniques and Best Practices

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From 59K ATP matches to a winner predictor (Random Forest)