Eric Khang'ati

Learning. Coding. Evolving.

Blog

Explore a curated collection of beginner-friendly machine learning projects and tutorials. Each article breaks down complex topics into simple, practical steps, from algorithms built with NumPy to real-world classification tasks, with code, visuals, and clear explanations for all learners.

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.

Linear Regression With NumPy: House Price Prediction

Predict house prices using a linear regression model built entirely with NumPy. This beginner project covers data prep, cost function, and gradient descent.

Logistic Regression for Email Spam Detection with NumPy

Build a spam detection model using logistic regression and NumPy. Learn how to process text data, apply the sigmoid function, and classify emails effectively.

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.

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.

Load More Articles