RoboInternWhat RoboIntern is
RoboIntern is a field guide to machine-learning models for predicting from historical data, with the Python included. You describe your data the way it already exists, as a list of columns: paste a header row and mark the target, the time column, series ids and your key drivers.
RoboIntern ranks the models that fit with a visible scoring formula, explains the maths of each, and writes train.py, predict.py and requirements.txt that you run on your own machine. Nothing runs on the site: it is a lookup dictionary with a code writer.
Who it's for: Analysts, developers and students who need to predict from historical data
What you can do
- Paste a header row; column types and roles are guessed
- Forecasting, regression, classification, anomaly detection and clustering
- A visible scoring formula that ranks every model that fits
- Plain explanations of the maths behind each model
- train.py, predict.py and requirements.txt, or a Jupyter notebook
- Optional cross-validated tuning with Optuna
Questions
Does RoboIntern see my data?
No. You describe the columns, not the rows; the code it writes runs on your own machine.
Which tasks does it cover?
Forecasting, regression, binary and multiclass classification, anomaly detection and clustering.
How are models ranked?
With a published score that weighs accuracy, interpretability and speed by the priorities you set, plus listed adjustments for your data.