OngoingOnline · Education · intermediate · data-science, machine-learning, python
Predict a hidden parameter of a nonlinear dynamical system from noisy, incomplete trajectory data. This competition tests skills in feature engineering, statistical analysis, and machine learning modeling on simulated sensor data.
OngoingOnline · Education · intermediate · machine-learning, classification, regression
A free online competition challenging participants to simultaneously cluster, classify, and regress on a large synthetic hardware tool dataset. It targets data scientists and students skilled in machine learning, Python, and multi-task modeling techniques.
OngoingOnline · Tech · intermediate · regression, data-science, machine-learning
A free online competition where participants build regression models to predict GPU performance metrics from hardware specifications. Targeted at data scientists and students skilled in Python and machine learning, this event focuses on tabular data analysis and minimizing RMSE e
OngoingOnline · Education · intermediate · machine-learning, regression, data-science
A free online hackathon qualifying participants for the DSN AI Bootcamp by building machine learning models to predict retail sales. Participants will perform data analysis, feature engineering, and regression modeling on real-world Nigerian retail data.
OngoingOnline · Education · intermediate · kaggle, regression, ordinal-regression
A free online competition where participants predict wine quality using regression on tabular data. Targeted at data scientists and students looking to practice ordinal regression and evaluation metrics like quadratic weighted kappa.
Registration openLaungowal · Tech · intermediate · machine-learning, web-development, classification
A hackathon-style competition where student teams solve water quality challenges by building ML models for classification and regression, then deploying a real-time web application with a REST API. Open to undergraduate and diploma students in India.
OngoingOnline · Education · intermediate · healthcare, machine-learning, data-science
A free online data science competition challenging participants to build AI models for estimating blood pressure from wearable PPG and ECG signals. Targeted at researchers and developers working in healthcare, machine learning, and signal processing.
OngoingOnline · Education · advanced · machine-learning, climate-science, kaggle
A Kaggle competition challenging participants to build ML models that emulate climate extremes using the NorESM2-MM dataset. Targeted at data scientists and researchers, it focuses on regression and probabilistic modeling skills to predict heat, drought, and flood indices.
Ongoing since 2018Online · Education · intermediate · kaggle, machine-learning, python
A free online competition for data science students and learners to practice predicting housing prices using regression techniques like random forest and gradient boosting. Participants apply feature engineering in R or Python to minimize RMSE errors on a dataset of Ames, Iowa ho
Ongoing since 2016Online · Education · intermediate · regression, machine-learning, python
A free data science competition where participants predict house prices in Ames, Iowa using advanced regression techniques. Designed for those with Python or R experience to practice feature engineering and machine learning models like random forests.
Ongoing since 2021Online · Education · intermediate · time-series-forecasting, machine-learning, data-science
A free Kaggle competition where participants use machine learning to forecast store sales for an Ecuadorian grocery retailer. It targets those practicing time-series forecasting and regression skills on real-world retail data.
Online · Education · intermediate · machine-learning, materials-science, prediction
An online hackathon where participants build ML models to predict polymer properties like Glass Transition Temperature using SMILES strings. Targeted at students and researchers in materials science, chemistry, or computer science looking to apply data-driven approaches to materi