Skip to main content

MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.

Project description

MindsDB

Build Status PyPI version

MindsDB's goal is to give developers easy access to the power of artificial neural networks for their projects.Tweet

MindsDB as project is made out of the following:

  • Mindsdb-native: This repository, which is a python module that aims for auto-model building, training, testing in a single line of code.

  • Lightwood: Under the hood of mindsdb native there is lightwood, a Pytorch based framework to streamline the work of gluing together building blocks for ML lightwood's GITHUB.

  • MindsDB Scout: A graphical user interface to work with MindsDB, with a focus on interpretability and explainability.

MindsDB Native

Try it out

Installation

You can use MindsDb on your own computer in under a minute, simply follow the installation instructions or, if you already have a python environment setup, just run:

 pip3 install mindsdb --user

You can try MindsDb on Google Colab

You can also use Docker to run mindsdb: sh -c "$(curl -sSL https://raw.githubusercontent.com/mindsdb/mindsdb/master/distributions/docker/build-docker.sh)"

If you'd prefer to watch a video tutorial, you can find it here. (Note: Please manually set it to 720p or greater to have the text appear clearly)

Having problems ? Please tell us about them with an issue on github

Usage

Once you have MindsDB installed, you can use it as follows:

To train a model:

from mindsdb import Predictor


# We tell mindsDB what we want to learn and from what data
Predictor(name='home_rentals_price').learn(
    to_predict='rental_price', # the column we want to learn to predict given all the data in the file
    from_data="https://s3.eu-west-2.amazonaws.com/mindsdb-example-data/home_rentals.csv" # the path to the file where we can learn from, (note: can be url)
)

To use the model:

from mindsdb import Predictor

# use the model to make predictions
result = Predictor(name='home_rentals_price').predict(when={'number_of_rooms': 2,'number_of_bathrooms':1, 'sqft': 1190})

# you can now print the results
print('The predicted price is ${price} with {conf} confidence'.format(price=result[0]['rental_price'], conf=result[0]['rental_price_confidence']))

Visit the documentation to learn more

Contributing

In order to make changes to mindsdb, the ideal approach is to fork the repository than clone the fork locally PYTHONPATH.

For example: export PYTHONPATH=$PYTHONPATH:/home/my_username/mindsdb.

To test if your changes are working you can try running the CI tests locally: cd tests/ci_tests && python3 full_test.py

Once you have specific changes you want to merge into master, feel free to make a PR.

Report Issues

Please help us by reporting any issues you may have while using MindsDB.

https://github.com/mindsdb/mindsdb/issues/new/choose

Project details


Release history Release notifications | RSS feed

This version

1.6.6

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

MindsDB-1.6.6.tar.gz (59.4 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page