MindsDB 0.9.1.0

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

#

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MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects. [](https://twitter.com/intent/tweet?text=Machine%20Learning%20in%20one%20line%20of%20code%21&url=https://www.mindsdb.com&via=mindsdb&hashtags=ai,ml,machine_learning,neural_networks)

* [Installing MindsDB](docs/Installing.md)
* [Learning from Examples](docs/examples/basic/README.md)
* [Frequently Asked Questions](docs/FAQ.md)
* [Provide feedback to improve MindsDB](https://mindsdb.typeform.com/to/c3CEtj)


## Quick Overview

You can get started in your own computer/cloud or you can also try it via your browser using [Google Colab](docs/GoogleColab.md).

It's very simple to set up

```bash
pip3 install mindsdb --user
```

[(Having issues? learn more)](docs/Installing.md)

Once you have MindsDB installed, you can use it as follows [(learn more)](docs/examples/basic/README.md):


To **train a model**:



```python

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="home_rentals.csv" # the path to the file where we can learn from, (note: can be url)
)

```


To **use the model**:


```python

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.predicted_values[0]['rental_price'], conf=result.predicted_values[0]['prediction_confidence']))

```

## Report Issues

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

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