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maxpumperla/elephas

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Elephas

Distributed Deep learning with Keras & Spark

Features

  • Deep Learning - Distributed deep learning using spark and neural network APIs.

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  • Deep Learning Ecosystems - Distributed deep learning with Keras and Spark.
  • Deep Learning Frameworks - Distributed deep learning with Keras and Spark.
  • Machine Learning Frameworks - Distributed deep learning with Keras and Spark.
  • Developer Tools - Distributed deep learning integration with Apache Spark.
  • 1,580 stars·306 forks·Python·MIT·7 views

    Star history

    Star history chart for maxpumperla/elephasStar history chart for maxpumperla/elephas

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Projects sharing features with Elephas

    These projects share indexed features with Elephas. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • maxpumperla/hyperasmaxpumperla avatar

      maxpumperla/hyperas

      2,178View on GitHub↗

      Keras Hyperopt: A very simple wrapper for convenient hyperparameter optimization

      Python
      View on GitHub↗2,178
    • pytorch/ignitepytorch avatar

      pytorch/ignite

      4,800View on GitHub↗

      Ignite is a high-level training framework for PyTorch neural networks that serves as a training engine and deep learning lifecycle manager. It provides a structured system for organizing and automating training and evaluation loops, managing data iterators and triggering event handlers at specific milestones during the model training process. The project distinguishes itself through a comprehensive suite of tools for distributed training and model evaluation. It includes utilities for synchronizing gradients and coordinating collective communication across multiple GPUs or nodes, as well as a

      Python
      View on GitHub↗4,800
    • catalyst-team/catalystcatalyst-team avatar

      catalyst-team/catalyst

      3,376View on GitHub↗

      Accelerated deep learning R&D

      Python
      View on GitHub↗3,376
    • cornellius-gp/gpytorchcornellius-gp avatar

      cornellius-gp/gpytorch

      3,893View on GitHub↗

      GPyTorch is a GPU-accelerated probabilistic framework and PyTorch library for implementing scalable Gaussian process models. It provides a system for Gaussian process modeling and uncertainty estimation, designed to perform efficient matrix operations on graphics hardware. The framework features a modular kernel system for constructing custom covariance functions and modeling complex data dependencies. It specifically integrates Gaussian processes with deep neural networks to create hybrid models for regression and classification. The system employs numerical linear algebra techniques, inclu

      Python
      View on GitHub↗3,893
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    Frequently asked questions

    What does maxpumperla/elephas do?

    Distributed Deep learning with Keras & Spark

    What are the main features of maxpumperla/elephas?

    The main features of maxpumperla/elephas are: Deep Learning, Deep Learning Ecosystems, Deep Learning Frameworks, Machine Learning Frameworks, Developer Tools.

    Which projects share features with maxpumperla/elephas?

    Projects with overlapping indexed features include: pytorch/ignite — Ignite is a high-level training framework for PyTorch neural networks that serves as a training engine and deep… maxpumperla/hyperas — Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization. catalyst-team/catalyst — Accelerated deep learning R&D. google/qkeras — QKeras: a quantization deep learning library for Tensorflow Keras. bsautermeister/tensorlight — TensorLight - A high-level framework for TensorFlow. cornellius-gp/gpytorch — GPyTorch is a GPU-accelerated probabilistic framework and PyTorch library for implementing scalable Gaussian process…