Decision Tree from Scratch with NumPy Explained Simply
Learn how to build a decision tree from scratch using NumPy. Understand entropy, information gain, and step-by-step model construction in Python.
Heart Failure Prediction Using SVM with Scikit-Learn Guide
Learn how to build a heart failure prediction model using SVM with Scikit-Learn. This step-by-step tutorial covers preprocessing, model training, and evaluation for beginners.
Build a Support Vector Machine From Scratch using Numpy
Learn how to build a Support Vector Machine (SVM) from scratch using NumPy. This guide explains the math, Hinge Loss, and Gradient Descent for beginners.
KNN with Scikit-Learn: A Heart Disease Prediction Guide
Learn how to build a heart disease prediction model using KNN with Scikit-Learn in Python. A beginner-friendly step-by-step guide.
KNN with NumPy: A Beginner’s Guide to K – Nearest Neighbors
Learn KNN with NumPy step-by-step. Build K-Nearest Neighbors from scratch for machine learning.
Predict Appointments — Logistic Regression with Scikit-Learn
Learn logistic regression with scikit-learn by predicting patient appointment no-shows. A beginner-friendly Machine Learning project with clear steps.
Polynomial Regression Scikit-Learn: Medical Cost Prediction
Predict medical expenses using regression models with polynomial regression. This project compares Linear, Ridge, and Lasso with cross-validation and tuning.
Exploratory Data Analysis, Feature Engineering & Hypothesis
Learn exploratory data analysis, feature engineering & hypothesis testing through Telco churn case study. Step-by-step Python guide for data science beginners.
Customer Churn Prediction With Random Forest and XGBoost
Better customer churn prediction is possible: See how we applied both Random Forest and XGBoost models to telecom data to anticipate cancellations in advance.
Decision tree explained through the Titanic dataset
A beginner-friendly guide to using decision trees for predicting Titanic survival, featuring step-by-step code, clear explanations, pruning, and evaluation.