DMTK vs Kubeflow vs Polyaxon
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Detailed Comparison
DMTK provides a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. | An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications. | The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions. |
DMTK Framework: a flexible framework that supports unified interface for data parallelization, hybrid data structure for big model storage, model scheduling for big model training, and automatic pipelining for high training efficiency.;
LightLDA, an extremely fast and scalable topic model algorithm, with a O(1) Gibbs sampler and an efficient distributed implementation.;
Distributed (Multisense) Word Embedding, a distributed version of (multi-sense) word embedding algorithm. | - | - |
Statistics | ||
GitHub Stars 2.7K | GitHub Stars 3.7K | GitHub Stars - |
GitHub Forks 559 | GitHub Forks 325 | GitHub Forks - |
Stacks 4 | Stacks 11 | Stacks 205 |
Followers 18 | Followers 65 | Followers 585 |
Votes 0 | Votes 14 | Votes 18 |
Pros & Cons | ||
No community feedback yet | Pros
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Integrations | ||
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What are some alternatives to DMTK, Polyaxon, Kubeflow?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
Streamlit
It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
MLflow
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
H2O
H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.
PredictionIO
PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
Gluon
A new open source deep learning interface which allows developers to more easily and quickly build machine learning models, without compromising performance. Gluon provides a clear, concise API for defining machine learning models using a collection of pre-built, optimized neural network components.
