lightwood | Lightwood is Legos for Machine Learning | Machine Learning library

 by   mindsdb Python Version: 23.12.4.0 License: GPL-3.0

kandi X-RAY | lightwood Summary

kandi X-RAY | lightwood Summary

lightwood is a Python library typically used in Artificial Intelligence, Machine Learning applications. lightwood has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install lightwood' or download it from GitHub, PyPI.

Lightwood is an AutoML framework that enables you to generate and customize machine learning pipelines declarative syntax called JSON-AI. Our goal is to make the data science/machine learning (DS/ML) life cycle easier by allowing users to focus on what they want to do their data without needing to write repetitive boilerplate code around machine learning and data preparation. Instead, we enable you to focus on the parts of a model that are truly unique and custom. Lightwood works with a variety of data types such as numbers, dates, categories, tags, text, arrays and various multimedia formats. These data types can be combined together to solve complex problems. We also support a time-series mode for problems that have between-row dependencies. Our JSON-AI syntax allows users to change any and all parts of the models Lightwood automatically generates. The syntax outlines the specifics details in each step of the modeling pipeline. Users may override default values (for example, changing the type of a column) or alternatively, entirely replace steps with their own methods (ex: use a random forest model for a predictor). Lightwood creates a "JSON-AI" object from this syntax which can then be used to automatically generate python code to represent your pipeline. For details on how to generate JSON-AI syntax and how Lightwood works, check out the Lightwood Philosophy.
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            kandi-support Support

              lightwood has a low active ecosystem.
              It has 369 star(s) with 82 fork(s). There are 11 watchers for this library.
              There were 1 major release(s) in the last 6 months.
              There are 49 open issues and 392 have been closed. On average issues are closed in 146 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of lightwood is 23.12.4.0

            kandi-Quality Quality

              lightwood has 0 bugs and 0 code smells.

            kandi-Security Security

              lightwood has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              lightwood code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              lightwood 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

              lightwood 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.

            Top functions reviewed by kandi - BETA

            kandi has reviewed lightwood and discovered the below as its top functions. This is intended to give you an instant insight into lightwood implemented functionality, and help decide if they suit your requirements.
            • Explain prediction of the model
            • Add confidence bounds
            • Assigns the timeseries to tss
            • Format row and global insights
            • Transform a timeseries into a DataFrame
            • Add next target to the dataframe
            • Determine if a row is a prediction
            • Calculate the number of processes
            • Compute anomaly detection
            • Normalizes numbers
            • Decode the given tensor
            • Train a model
            • Calibrate the calibration
            • Guess the type of a sequence
            • Evaluate the Categorical accuracy
            • Calculate the confidence interval accuracy
            • Predict the confidence value of x
            • Wrapper for mut_mut_method
            • R Evaluate the regression accuracy
            • Perform the analysis
            • Explain prediction
            • Analyze block
            • Perform validation
            • Analyze timeseries
            • Encodes the data into a list of floats
            • Splits the data
            Get all kandi verified functions for this library.

            lightwood Key Features

            No Key Features are available at this moment for lightwood.

            lightwood Examples and Code Snippets

            No Code Snippets are available at this moment for lightwood.

            Community Discussions

            QUESTION

            castShadow and recieveShadow is not rendering in the scene
            Asked 2020-Jun-09 at 11:22

            I am learning threejs by doing some games. I am able to render all models in the scene and added few lights to and it is perfect now, but when I try to cast and recieve shadows on the plane. The shadows of the objects in scene are not rendering.

            I dont understand where I am doing wrong.

            Below is the code

            Please have a look and help me resolving the issue.

            ...

            ANSWER

            Answered 2020-Jun-09 at 11:22

            I've tested your code offline and there are multiple issue and runtime errors:

            • AmbientLight does not cast shadows. Setting castShadow will produce a runtime error.
            • You have not configured the shadow frustum for your instance of DirectionalLight correctly. Try it with this code:

            Source https://stackoverflow.com/questions/62280231

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

            Vulnerabilities

            No vulnerabilities reported

            Install lightwood

            You can install Lightwood as follows:. Note: depending on your environment, you might have to use pip instead of pip3 in the above command. However, we recommend creating a python virtual environment. If python default to python2.x on your environment use python3 and pip3 instead. Currently, the preferred environment for working with lightwood is visual studio code, a very popular python IDE. However, any IDE should work. While we don't have guides for those, please feel free to use the following section as a template for VSCode, or to contribute your own tips and tricks to set up other IDEs.
            Clone lightwood
            cd lightwood && pip install -r requirements.txt
            Add it to your python path (e.g. by adding export PYTHONPATH='/where/you/cloned/lightwood':$PYTHONPATH as a newline at the end of your ~/.bashrc file)
            Check that the unittests are passing by going into the directory where you cloned lightwood and running: python -m unittest discover tests
            Install and enable setting sync using github account (if you use multiple machines)
            Install pylance (for types) and make sure to disable pyright
            Go to Python > Lint: Enabled and disable everything but flake8
            Set python.linting.flake8Path to the full path to flake8 (which flake8)
            Set Python › Formatting: Provider to autopep8
            Add --global-config=<path_to>/lightwood/.flake8 and --experimental to Python › Formatting: Autopep8 Args
            Install live share and live share whiteboard

            Support

            We love to receive contributions from the community and hear your opinions! We want to make contributing to Lightwood as easy as it can be.
            Find more information at:

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            Install
          • PyPI

            pip install lightwood

          • CLONE
          • HTTPS

            https://github.com/mindsdb/lightwood.git

          • CLI

            gh repo clone mindsdb/lightwood

          • sshUrl

            git@github.com:mindsdb/lightwood.git

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