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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. Deepchecks vs Polyaxon

Deepchecks vs Polyaxon

OverviewComparisonAlternatives

Overview

Polyaxon
Polyaxon
Stacks11
Followers65
Votes14
GitHub Stars3.7K
Forks325
Deepchecks
Deepchecks
Stacks2
Followers2
Votes0
GitHub Stars3.9K
Forks288

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Detailed Comparison

Polyaxon
Polyaxon
Deepchecks
Deepchecks

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

It is a Python package for comprehensively validating your machine learning models and data with minimal effort. This includes checks related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.

-
Suites of checks; Data integrity; Distribution checks; Performance checks
Statistics
GitHub Stars
3.7K
GitHub Stars
3.9K
GitHub Forks
325
GitHub Forks
288
Stacks
11
Stacks
2
Followers
65
Followers
2
Votes
14
Votes
0
Pros & Cons
Pros
  • 2
    API
  • 2
    Python Client
  • 2
    Notebook integration
  • 2
    Tensorboard integration
  • 2
    Streamlit integration
No community feedback yet
Integrations
Docker
Docker
Kubernetes
Kubernetes
Helm
Helm
Python
Python
Jupyter
Jupyter
Caffe2
Caffe2
TensorFlow
TensorFlow
Keras
Keras
Gluon
Gluon
Python
Python

What are some alternatives to Polyaxon, Deepchecks?

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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