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RRishikantrishiii2.hashnode.dev4d ago · 7 min read

Conquering Tabular Data: Decision Trees, Random Forests, and the Math of XGBoost

So far in this series, we have focused entirely on algorithms that draw smooth, continuous curves through data—Linear Regression, Logistic Regression, and Deep Neural Networks. These models are the un

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Ddanieljasmedanieljasme.hashnode.devMay 27 · 9 min read

Building a Near-Perfect Claims Classifier: Random Forest vs XGBoost on TikTok Data (Google Advanced DA Course 5)

This is the fourth and final post in my Google Advanced Data Analytics Certificate series on the TikTok claims classification project. Part 1: data inspection. Part 2: EDA and visualization. Part 3: h

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WTwajahat tajai-ml-datascience-from-scratch.hashnode.devMay 19 · 11 min read

Building CivicAI : Part 2: Training the ML Pipeline That Powers It All

Series: Building an AI-Powered Municipal Complaint Management System from Scratch Where We Left Off In Part 1, we built our dataset from scratch — growing it from 200 raw records to a clean, label-ri

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YPYejun Parkyejunpark3.hashnode.devMay 11 · 14 min read

From One Tree to a Forest: A Practical Guide to Ensemble Methods in Machine Learning

You've trained your decision tree. It fits your training data beautifully — almost suspiciously well. Then you test it on new data, and it falls apart. Sound familiar? This is the classic overfitting

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AAArjun Adhikariblogs.thearjun.comMay 9 · 7 min read

Why Your ML Model Is Either Stubborn or Paranoid and How to Fix It

You've shipped a model. It looks great on your training data. You put it in production and it falls apart. Or maybe the opposite, it works sometimes, wildly fails other times, with no pattern you can

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AAAbstract Algorithmsabstractalgorithms.devMar 29 · 18 min read

Ensemble Methods: Random Forests, Gradient Boosting, and Stacking Explained

TLDR: 🌲 Ensemble methods combine multiple "weak" learners to create stronger predictors. Random Forest uses bootstrap sampling + feature randomization. Gradient Boosting sequentially corrects errors.

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IEIfeanyi Ezeriohagodwithus.hashnode.devMar 2 · 16 min read

Decision Trees, Random Forests, and the Art of Knowing When Simple Is Enough

Week 18 of my data science internship at DataraFlow shifted the focus from distance-based and probabilistic classifiers to tree-based methods; a family of algorithms that don't just predict outcomes,

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DDeepikafrom-idea-to-code.hashnode.devFeb 25 · 5 min read

From Jupyter Notebooks to Production: Mistakes I Made Building an ML App

I built an employee attrition predictor. Random Forest, 83% accuracy, clean notebooks. Wrapped it in FastAPI, tested it... and it predicted "Stay" for everyone. This is what I learned debugging my way

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SSSanjana Shyamsundarblogs.codechefvit.comFeb 22 · 7 min read

Capital One’s 200ms Random Forest: Stopping Launderers Before the Wire Hits

Imagine spotting a money launderer before the wire transaction even settles! Capital One’s ML model just turned a traditional 30 page rulebook into a 200 ms risk score that tells investigators which g

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OEOGUNYEMI EZEKIEL TIMILEHINogunyemi-ezekiel-timilehin.hashnode.devFeb 17 · 7 min read

End-to-End Employee Attrition Prediction System

Decision Tree & Random Forest Classification Employee attrition is one of the most expensive silent risks in any organization. Replacing talent costs money, time, productivity, and morale. In this project, I built a complete machine learning pipeline...

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#random-forest

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Trending tags this week

Conquering Tabular Data: Decision Trees, Random Forests, and the Math of XGBoost

Building a Near-Perfect Claims Classifier: Random Forest vs XGBoost on TikTok Data (Google Advanced DA Course 5)

Building CivicAI : Part 2: Training the ML Pipeline That Powers It All

From One Tree to a Forest: A Practical Guide to Ensemble Methods in Machine Learning

Why Your ML Model Is Either Stubborn or Paranoid and How to Fix It

Ensemble Methods: Random Forests, Gradient Boosting, and Stacking Explained

Decision Trees, Random Forests, and the Art of Knowing When Simple Is Enough

From Jupyter Notebooks to Production: Mistakes I Made Building an ML App

Capital One’s 200ms Random Forest: Stopping Launderers Before the Wire Hits

End-to-End Employee Attrition Prediction System