#sklearn articles

AAkashakashbuilds.hashnode.devAug 5 · 12 min read

Building Production-Ready ML Models: From Data to Deployment

I originally built these projects in college for learning purposes, and I’m sharing them now to pass along the experience and lessons I gained Machine learning projects often fail not because of poor

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Ddanieljasmedanieljasme.hashnode.devMay 27 · 7 min read

From Hypothesis Testing to Logistic Regression: TikTok Claims Project (Google Advanced DA — Courses 3 & 4)

This is the third post in my Google Advanced Data Analytics Certificate series, documenting the TikTok claims classification project. Part 1 covers initial data inspection (Course 1). Part 2 covers ED

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PPrachiml-learning-blog.hashnode.devApr 8 · 11 min read

Episode 1: Mastering NumPy

Learning ML from scratch Series intro: This is the first post in ML from Scratch — a series where we build everything from the ground up, no black boxes. Before we touch PyTorch or scikit-learn, we n

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AZAyomide Zaccheauspapizee.hashnode.devFeb 17 · 15 min read

Week 18: My Model Got 100% Again — And This Time I Didn't Celebrate

Last week, I got my first real taste of classification algorithms. I worked through K-Nearest Neighbours (KNN), Support Vector Machines (SVM), and Naive Bayes — three very different approaches to the same core problem: teaching a computer to sort thi...

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AKArun Kumarimportarun-dl.hashnode.devFeb 15 · 7 min read

Zero to Neuron Series 8: The Goldilocks Dilemma—Overfitting, Underfitting, and Tuning

We've done the analogies. We've done the math. We've even made the GPU sweat. But here is the hard truth about Machine Learning: Just because your model runs, doesn't mean it’s learning. A model is li

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ASadarsh singhthe-ml-script.hashnode.devFeb 1 · 4 min read

The ML Script : Week 2

Hello World! It feels nice to come back after a week, open Hashnode, and write about my experience. This past week was not quite as productive as Week 1 was, but it's fine—who cares? Progress is progress. This week, I dove into Linear Regression (LR)...

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ACAngelic Charlesnerdyalgorithm.hashnode.devJan 26 · 25 min read

Week 16 with Dataraflow: My Journey Through Advanced Machine Learning - Random Forests, Classification, and Customer Churn Prediction

Introduction Week 16 with Dataraflow was a transformative experience in my data science journey. This wasn't just about running algorithms, it was about truly understanding the "Fail & Fix" philosophy that turns errors into powerful learning opportun...

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AIAbdulquadri Isholamy-journey-into-data-science-ml-and-ai.hashnode.devJan 5 · 4 min read

From Exploring Data to Predictions: My 14th Week at DataraFlow

Ever stared at a spreadsheet and wondered, "What if this data could tell me what comes next?" That was the feeling that defined Week 14 at DataraFlow. This wasn’t just about analysing what had already happened. This was the week I crossed a subtle bu...

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IEIfeanyi Ezeriohagodwithus.hashnode.devDec 24, 2025 · 10 min read

Mastering Data Preprocessing and Regression Analysis: A Comprehensive Take-Home Project

As a data science intern at DataraFlow, I've had the opportunity to dive deep into the fundamentals of data preprocessing and regression analysis through this intensive take-home assignment. My solution represents a complete walkthrough of essential ...

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MMMohamad Mahmoodshortnotes.razzi.myDec 14, 2025 · 5 min read

SKlearn Vs MLJS

What if you could choose the perfect machine learning tool for your project — would you go with the robust, feature-rich scikit-learn or the lightweight, web-friendly ml package? Both scikit-learn (Python) and the ml package (JavaScript) are popular ...

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