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ML Arena 1 - Linear Regression

This folder is a dedicated repo-style package for Problem 1: Linear Regression.

This repository is part of the ML Arena family, a set of 5 dedicated repositories where each repository focuses on one core ML problem.

ML Arena Family Repositories

  • ML-Arena-1 - Linear Regression (Current Repo)
  • ML-Arena-2 - Logistic Regression
  • ML-Arena-3 - Decision Tree
  • ML-Arena-4 - K-Means Clustering
  • ML-Arena-5 - Neural Network

Dataset

  • File: dataset.csv
  • Source: UCI Concrete Compressive Strength
  • Rows: 1030
  • Columns: 9 (8 input features + 1 target)
  • Target: Concrete compressive strength

Repository Layout

Linear-Regression/
├─ README.md
├─ CONTRIBUTING.md
├─ dataset.csv
├─ exploration/
│  └─ exploration.ipynb
├─ library/
│  └─ training.ipynb
├─ scratch/
│  └─ training.ipynb
└─ PULL_REQUEST_TEMPLATE.md

Task Tracks

  • Exploration: Data understanding, distributions, correlation, and insights.
  • Library: Baseline model with standard ML libraries.
  • Scratch: First-principles implementation using NumPy.
  • Optimization: Improvements on top of library or scratch baseline.

Contribution Model

Each issue is open to multiple contributors.

  • Multiple PRs can be submitted for the same issue.
  • Different approaches, implementations, and optimizations are welcome.

This means even if someone has already submitted a PR for an issue, you are still encouraged to submit your own solution.

Quick Start

  1. Fork this folder as its own repo (Linear-Regression).
  2. Clone your fork and create a branch.
  3. Pick one issue.
  4. Work in only one notebook per issue based on track:
    • exploration/exploration.ipynb
    • library/training.ipynb
    • scratch/training.ipynb
  5. Run all cells top to bottom.
  6. Open a pull request with Closes #<issue-number>.

See CONTRIBUTING.md for detailed rules.