Nov 11, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today, I explored Support Vector Machines (SVMs) — a powerful algorithm that can classify data by finding the best possible boundary between classes. After spending the last few days learning about ensemble methods and b...
Join discussionNov 10, 2025 · 2 min read · Hey everyone 👋 Dhairya here, After exploring Random Forest and AdaBoost yesterday, today I took a deeper dive into Gradient Boosting and XGBoost — algorithms that form the backbone of many Kaggle-winning solutions. These models are all about learnin...
Join discussionNov 9, 2025 · 2 min read · Hey everyone 👋 Dhairya here, I’m back after a long time took a break bacause of festive season and college exams and all i was unable to give time to learn and did not want to force things else i wont learn properly you know. After learning about hy...
Join discussionSep 15, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today I took another big step in ML by learning hyperparameter tuning. After evaluating models with cross-validation, I realized that picking the right hyperparameters is just as important as choosing the model itself. ...
Join discussionSep 8, 2025 · 2 min read · Hey everyone 👋 Dhairya here, After building my first ML models yesterday, I realized: training a model is easy, but properly evaluating it is the real challenge. Today, I focused on evaluation metrics and cross-validation to ensure that models are n...
Join discussionSep 7, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today was a huge milestone in my journey — I built my first real machine learning models using Scikit-Learn! Until now, my focus was mostly on math, probability, and preprocessing data. Today, I finally got to see theory...
Join discussionSep 6, 2025 · 2 min read · Hey everyone 👋 Dhairya here, Today, I moved from pure math and probability into practical machine learning work using Scikit-Learn. Before training any model, the data needs to be cleaned, transformed, and preprocessed — and that’s what I focused on...
Join discussionSep 1, 2025 · 2 min read · Hey everyone 👋, Dhairya here. Today marks a special milestone in my AI/ML Internship Prep Challenge — I started working with Scikit-Learn (sklearn), one of the most important libraries in the ML ecosystem. After building up the math and probability ...
Join discussionAug 28, 2025 · 2 min read · 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)=...
Join discussionAug 27, 2025 · 2 min read · Hey everyone 👋 Dhairya here, On Day 6, I explored the basics of probability distributions (Bernoulli, Binomial, Normal, Uniform). Today, I took it a step further and studied how these distributions are applied in actual ML models and algorithms. 🔢...
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