MindsDB's goal is to give developers easy access to the power of artificial neural networks for their projects.
- Installing MindsDB
- Learning from Examples
- Frequently Asked Questions
- Provide Feedback to Improve MindsDB
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 --userYou can try MindsDb on Google Colab
You can also use the Docker image here
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 porlbems ? Please tell us about them with an issue on github
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
Please help us by reporting any issues you may have while using MindsDB.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent