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  1. Stackups
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  4. Machine Learning Tools
  5. Polyaxon vs Swift AI

Polyaxon vs Swift AI

OverviewComparisonAlternatives

Overview

Swift AI
Swift AI
Stacks14
Followers52
Votes0
Polyaxon
Polyaxon
Stacks11
Followers65
Votes14
GitHub Stars3.7K
Forks325

Polyaxon vs Swift AI: What are the differences?

Developers describe Polyaxon as "An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications". An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications. On the other hand, Swift AI is detailed as "A.I. and machine learning library written in Swift". Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!.

Polyaxon and Swift AI can be categorized as "Machine Learning" tools.

Swift AI is an open source tool with 5.58K GitHub stars and 542 GitHub forks. Here's a link to Swift AI's open source repository on GitHub.

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Detailed Comparison

Swift AI
Swift AI
Polyaxon
Polyaxon

Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Feed-Forward Neural Network; Fast Matrix Library
-
Statistics
GitHub Stars
-
GitHub Stars
3.7K
GitHub Forks
-
GitHub Forks
325
Stacks
14
Stacks
11
Followers
52
Followers
65
Votes
0
Votes
14
Pros & Cons
No community feedback yet
Pros
  • 2
    API
  • 2
    Python Client
  • 2
    Notebook integration
  • 2
    Tensorboard integration
  • 2
    Streamlit integration
Integrations
Swift
Swift
Docker
Docker
Kubernetes
Kubernetes
Helm
Helm
Python
Python
Jupyter
Jupyter
Caffe2
Caffe2
TensorFlow
TensorFlow
Keras
Keras
Gluon
Gluon

What are some alternatives to Swift AI, Polyaxon?

TensorFlow

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

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

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

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

Kubeflow

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.

TensorFlow.js

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

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

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

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

PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.

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