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Initial time range – from 10 Feb, 2023 to 13 May, 2023

Final time range – from 11 Nov, 2023 to 10 Feb, 2024

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Summary of numerai/example-scripts

The numerai/example-scripts is a GitHub repository related to the Numerai project. Numerai is a hedge fund that uses data science tournaments to manage its assets. The repository provides example scripts that help users understand how to interact with Numerai's data.

The scripts are generally provided in Python and cover a broad range of stages in the data science workflow, including data loading, feature selection, model training, prediction generation, and results submission. There is also comprehensive guidance on how to use the Numerai API to automate parts of the workflow.

The repository contains the following key scripts:

  • Provides a simple example of a model that can be trained on Numerai data.
  • Shows how to generate predictions using a trained model and upload these predictions to Numerai.
  • Demonstrates how to combine multiple models into an ensemble for improved prediction accuracy.
  • Shows how to perform a backtest to simulate the performance of a model on historical data.

The repository is regularly updated by the Numerai team to ensure that the scripts remain current and useful.

# [Numerai Example Scripts]( Numerai is a hedge fund that hosts regular data science competitions. This repository gives users a starting point for how to work with an interact with Numerai's data. It provides example scripts on data loading, preprocessing, model training, prediction generation, and submission. The scripts can serve as a starting point for users to build their own models or tools. The repository also provides convenience methods for interacting with the Numerai API, such as submitting predictions or retrieving past tournament results. The scripts are mainly written in Python and users are encouraged to adapt them to their own needs. Key scripts in the repository include: - ``: A simple script that trains a model on Numerai's training data and makes predictions on the tournament data. - ``: This script generates predictions from the model trained in `` and submits the predictions to Numerai's servers. - ``: This script shows an example of how to combine predictions from multiple models into an ensemble, which can often lead to improved prediction accuracy over a single model. - ``: This script shows how to perform a backtest, which simulates the performance of the model on past tournaments.

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