The book every data scientist needs on their desk.

Landscape of ML/DL performance evaluation metrics

Regression Metrics Calculation Made easy for tensorflow2 and scikit-learn

This repository contains an exercise on regression metrics using an income dataset to predict happiness. The exercise includes data preprocessing, model training, evaluation, and visualization.

Regression is a statistical method used to analyze the relationship between one or more independent variables (often referred to as predictors, features, or input variables) and a dependent variable (often referred to as the target, response, or output variable). Scaling is the process of transforming data so that it falls within a specific range.

Brain tumour detector built with YOLOv8 model.

evaluation metrics implementation in Python from scratch

Regression exercises and projects done at alx training

Boston Housing Price prediction using regressions

Rent pricing prediction on NY properties with interactive dashboards.

Supervised Learning project from TripleTen

Your all-in-one Machine Learning resource – from scratch implementations to ensemble learning and real-world model tuning. This repository is a complete collection of 25+ essential ML algorithms written in clean, beginner-friendly Jupyter Notebooks. Each algorithm is explained with intuitive theory, visualizations, and hands-on implementation.