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Machine Learning
CodeRush 2026Machine Learning

Machine Learning

Data → Model → Podium.

2–3 members
Wed May 6 → Fri May 8 (submission) · Evals Sun May 10
Online (remote development + Kaggle submission)
Prizes
1st PlacePKR 15,000
2nd PlacePKR 10,000

Overview

An end-to-end hackathon challenge where teams act as Data Scientists to solve a real-world problem using Classification, Regression, or NLP. Teams must move from raw data to a deployable model — fully online.

Tournament Workflow

  • Kickoff — Wednesday, May 6: Problem statement, dataset, and test inputs released. Teams begin remote development.
  • Submission Deadline — Friday, May 8 (Night): Teams upload predictions to a private Kaggle leaderboard + push code to GitHub.
  • Shortlisting: Top teams advance based on leaderboard metrics (Accuracy, F1, RMSE).
  • Evaluations — Sunday, May 10: Final code review and approach evaluation by the jury.

Logistics & Environment

  • Format: Fully online — develop from anywhere.
  • Languages Allowed: Python (Primary), R.
  • Software: Jupyter Notebooks, Google Colab, Kaggle Kernels.
  • Final evaluations on Sunday, May 10 (online or hybrid as per jury).

AI Policy & Submission

  • AI: ALLOWED for boilerplate/debugging, but logic and analysis must be original.
  • Restrictions: No plagiarism from public GitHub repos. No external consultation.
  • Submission: Predictions on Kaggle + Code pushed to GitHub + final report via Google/GitHub Classroom by Friday night.

Marking Criteria

  • Algorithm Logic: Preference for elegant, simple solutions.
  • Data Analysis: Quality of EDA, visualizations, and correlation insights.
  • Presentation: Technical defense, clarity, and handling of the Hidden Test Set.

Registrations Closed

The deadline has passed. See the schedule for venue + report time.

Closed