mindsdb | Enabling developers | Machine Learning library

 by   mindsdb Python Version: License: GPL-3.0

kandi X-RAY | mindsdb Summary

kandi X-RAY | mindsdb Summary

mindsdb is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning applications. mindsdb has no bugs, it has build file available, it has a Strong Copyleft License and it has high support. However mindsdb has 1 vulnerabilities. You can install using 'pip install mindsdb' or download it from GitHub, PyPI.
MindsDB enables you to use ML predictions in your database using SQL.

            kandi-support Support

              mindsdb has a highly active ecosystem.
              It has 16259 star(s) with 2041 fork(s). There are 366 watchers for this library.
              There were 10 major release(s) in the last 6 months.
              There are 572 open issues and 2243 have been closed. On average issues are closed in 84 days. There are 52 open pull requests and 0 closed requests.
              It has a negative sentiment in the developer community.
              The latest version of mindsdb is

            kandi-Quality Quality

              mindsdb has 0 bugs and 0 code smells.

            kandi-Security Security

              mindsdb has 1 vulnerability issues reported (0 critical, 1 high, 0 medium, 0 low).
              mindsdb code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              mindsdb is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              mindsdb releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 16128 lines of code, 875 functions and 226 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed mindsdb and discovered the below as its top functions. This is intended to give you an instant insight into mindsdb implemented functionality, and help decide if they suit your requirements.
            • performs a query
            • Parse the query .
            • Select data from a table .
            • Create a datasource .
            • Start the application .
            • Parses the sql statement as an insert statement .
            • Runs the loop .
            • Make a prediction .
            • Downloads the GUI .
            • Add an integration .
            Get all kandi verified functions for this library.

            mindsdb Key Features

            Automatic data pre-processing, feature engineering and encoding
            Classification, regression, time-series tasks
            Bring models to production without “traditional deployment” as AI Tables
            Get mModels’ accuracy scoring and confidence intervals for each prediction
            Join ML models with existing data
            Anomaly detection
            Model explainability analysis
            GPU support for models’ training
            Open JSON-AI syntax to build models and bring your own ML blocks in a declarative way
            REST API available as well

            mindsdb Examples and Code Snippets

            You can use below methods
            Pythondot img1Lines of Code : 44dot img1License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            cd $HOME
            mkdir Informix
            cd Informix
            mkdir -p home/informix/cli
            wget https://hcl-onedb.github.io/odbc/OneDB-Linux64-ODBC-Driver.tar
            sudo tar xvf  OneDB-Linux64-ODBC-Driver.tar -C ./home/informix/cli
            rm OneDB-Linux64-ODBC-Driver.tar
            export INFORMIXD  
            Using mongodb handler and server-Using predictor:
            Pythondot img2Lines of Code : 39dot img2License : Strong Copyleft (GPL-3.0)
            copy iconCopy
              {'type': 'house', 'sale_date': ISODate("2018-03-31T00:00:00.000Z")} 
                "collection": "mongo_int.house_sales", 
                "query":  { 
                    'type': 'house',
                    "sale_date": {"$gt": ISODate("2018-03-  
            Teradata Handler-Usage
            Pythondot img3Lines of Code : 38dot img3License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            DATABASE HR
            AS PERMANENT = 60e6, -- 60MB
               SPOOL = 120e6; -- 120MB
            SET TABLE HR.Employees (
               GlobalID INTEGER,
               FirstName VARCHAR(30),
               LastName VARCHAR(30),
               DateOfBirth DATE FORMAT 'YYYY-MM-DD',
               JoinedDate DATE FORMAT 'YY  
            Can Mindsdb predict a new row based on previous rows?
            Pythondot img4Lines of Code : 23dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            col1, col2
            1       2
            4       8
            16      32
            64      128
            col1, col2, col1_next, col2_next
            1       2       4           8
            4       8       16          32
            16      32      64          128
            col1, col
            How to specify pytorch as a package requirement on windows?
            Pythondot img5Lines of Code : 5dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            # ...
            torch===1.4.0  --find-links https://download.pytorch.org/whl/torch_stable.html
            torchvision===0.5.0  --find-links https://download.pytorch.org/whl/torch_stable.html
            # ...
            ImportError: cannot import name 'SimpleImputer'
            Pythondot img6Lines of Code : 4dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
             pip install -U scikit-learn
            from sklearn.impute import SimpleImputer

            Community Discussions


            Can Mindsdb predict a new row based on previous rows?
            Asked 2020-Mar-18 at 14:05

            I am experimenting with Mindsdb, a program to do machine learning with a few codes.

            So far as per my understanding after reading their tutorial docs, I assume that this program is to predict a new element of a new row of a table (in an excel file like csv, xlxs, etc), with a massive quantity of rows that are in the same format above it as data. It learns from the "data" and set up an algorithm to predict a new element (new column) of the new row, with a/some known (pre-given) value of element (column) in that row.

            I wonder if it can predict an entire new row without knowing any element's value of that row, only based on the previous rows. I asked Mindsdb on the main page (email), facebook, youtube and got no answer.

            If anyone is using Mindsdb and understand it, do you know if Mindsdb is able to do that?



            Answered 2020-Mar-17 at 14:19

            It's not possible to predict a new row per say, but you can format your data in such a way as to achieve this.

            Let's say you have the following data:

            Source https://stackoverflow.com/questions/60720572

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install mindsdb

            To install the latest version of MindsDB please pull the following Docker image:.
            To get your hands on MindsDB, we recommend using the Docker image or simply sign up for a free cloud account. Feel free to browse documentation for other installation methods and tutorials.


            You can find the complete documentation of MindsDB at docs.mindsdb.com. Documentation for our HTTP API can be found at apidocs.mindsdb.com.
            Find more information at:

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          • PyPI

            pip install MindsDB

          • CLONE
          • HTTPS


          • CLI

            gh repo clone mindsdb/mindsdb

          • sshUrl


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