The book every data scientist needs on their desk.
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Updated
Sep 17, 2025 - Jupyter Notebook
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
Brain tumour detector built with YOLOv8 model.
evaluation metrics implementation in Python from scratch
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.
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.
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.
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
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