ydata-synthetic | Synthetic data generators for tabular and time-series data | Machine Learning library

 by   ydataai Jupyter Notebook Version: 1.4.0 License: MIT

kandi X-RAY | ydata-synthetic Summary

kandi X-RAY | ydata-synthetic Summary

ydata-synthetic is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Generative adversarial networks applications. ydata-synthetic has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Synthetic data is artificially generated data that is not collected from real world events. It replicates the statistical components of real data without containing any identifiable information, ensuring individuals' privacy.
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              ydata-synthetic has a medium active ecosystem.
              It has 996 star(s) with 205 fork(s). There are 23 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 22 open issues and 54 have been closed. On average issues are closed in 68 days. There are 11 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of ydata-synthetic is 1.4.0

            kandi-Quality Quality

              ydata-synthetic has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              ydata-synthetic is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              ydata-synthetic releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.
              It has 1769 lines of code, 165 functions and 43 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed ydata-synthetic and discovered the below as its top functions. This is intended to give you an instant insight into ydata-synthetic implemented functionality, and help decide if they suit your requirements.
            • Train the model
            • Get batch data
            • Computes the discriminator loss
            • Define the network
            • Fit the GAN model
            • Run checkpoint
            • Validate the label column
            • Prepare the data processor
            • Download and cache a resource file
            • Get the project root
            • Return the path to the data directory
            • Fit the model
            • Define the generator
            • Get a batch of data from train
            • Load data from a CSV file
            • This function is used to process the real data
            • Build the network
            • Create a network
            • Train the discriminator
            • Download a file
            • Generate synthetic samples
            • Build the discriminator layer
            • Return a colormap
            • Build the embedderor
            Get all kandi verified functions for this library.

            ydata-synthetic Key Features

            No Key Features are available at this moment for ydata-synthetic.

            ydata-synthetic Examples and Code Snippets

            No Code Snippets are available at this moment for ydata-synthetic.

            Community Discussions

            Trending Discussions on ydata-synthetic

            QUESTION

            Combine Models (outputs) in Keras
            Asked 2021-Nov-09 at 15:16

            I'm trying to build the networks presented in the following paper: link

            Basically, the autoencoder is a composition of two other models, embedder and recovery described below:

            ...

            ANSWER

            Answered 2021-Nov-09 at 15:15

            The problem is that embedder and recovery are not models with trainable_variables. Those two functions simply return the output of the last layer. Maybe try something like this:

            Source https://stackoverflow.com/questions/69900375

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

            Vulnerabilities

            No vulnerabilities reported

            Install ydata-synthetic

            The source code is currently hosted on GitHub at: https://github.com/ydataai/ydata-synthetic. Binary installers for the latest released version are available at the Python Package Index (PyPI).

            Support

            We are open to collaboration! If you want to start contributing you only need to:.
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            Install
          • PyPI

            pip install ydata-synthetic

          • CLONE
          • HTTPS

            https://github.com/ydataai/ydata-synthetic.git

          • CLI

            gh repo clone ydataai/ydata-synthetic

          • sshUrl

            git@github.com:ydataai/ydata-synthetic.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link