MindsDB Beginner Guide
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Nov 24, 2024
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docx
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Uploaded by ProfessorIceCat10
MindsDB Beginner Guide
1. Install MindsDB
You can install MindsDB locally or in the cloud.
Local installation
To install MindsDB locally, you will need to have Python 3.6 or higher installed. You can install MindsDB using the following command:
Cloud installation
To install MindsDB in the cloud, you can use the MindsDB Cloud Demo. To do this, visit the MindsDB website and click on the "Try MindsDB Cloud" button.
2. Create a MindsDB database
Once you have installed MindsDB, you can create a database using the following command:
3. Connect to the MindsDB database
You can connect to the MindsDB database using a SQL client such as MySQL Workbench or pgAdmin.
To connect using MySQL Workbench:
1.
Open MySQL Workbench.
2.
Click on the "New Connection" button.
3.
In the "Connection details" section, enter the following information:
o
Host: localhost
o
Port: 3306
o
Username: root
o
Password: mindsdb
o
Database: my_database
4.
Click on the "Test Connection" button.
5.
If the connection is successful, click on the "OK" button.
To connect using pgAdmin:
1.
Open pgAdmin.
2.
Click on the "Create" button.
3.
Select "Server" from the list of options.
4.
In the "Server Properties" dialog box, enter the following information:
o
Name: MindsDB
o
Hostname: localhost
o
Port: 5432
o
Username: postgres
o
Password: mindsdb
5.
Click on the "Save" button.
4. Load data into the MindsDB database
Once you have connected to the MindsDB database, you can load data into it using the following command:
5. Create a MindsDB model
To create a MindsDB model, you can use the following command:
This will create a new MindsDB model with the name my_model
. You can then train the model on your data using the following command:
6. Make predictions with a MindsDB model
Once you have trained a MindsDB model, you can use it to make predictions on new data using
the following command:
This will create a new file called my_predictions.csv
that contains the predictions made by the model.
Here is an example of how to use MindsDB to predict the price of a house:
This will create a new file called house_price_predictions.csv
that contains the predictions made
by the model.
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