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  3. Multi-Class Prediction of Obesity Risk
KaggleTime SeriesIntermediateRegistration open

Multi-Class Prediction of Obesity Risk

A intermediate time series competition requiring roughly 15–45 hours for an end-to-end practice run.

Difficulty
Intermediate
Estimated effort
15–45 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

Intermediate learners who want to deepen their skills in general machine learning. Good for building practical experience with real-world data.

Read the original official blurb
Playground Series - Season 4, Episode 2

Preparation

From registration to a first submission

  1. 01

    Python

  2. 02

    scikit-learn or similar ML library

  3. 03

    data analysis with pandas

Before you commit: Requires solid machine learning fundamentals and good experimental methodology.

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
Kaggle
Last checked
Feb 1, 2024

Entry assessment

est.
36

Prepare before joining

Overall fit estimate

Beginner fit36/100
Learning value68/100

Confirm eligibility and time commitment before moving into formal preparation.

18+ · Location rules

Open official pageSign in to saveOpen guide

Timeline

Registration opens
Feb 1, 2024
Submission deadline
Feb 29, 2024
Competition ends
Feb 29, 2024

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Feb 1, 2024
Source created
Jan 30, 2024
Published on this site
Jul 18, 2026