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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. Microsoft Cognitive Toolkit vs Tensorpack

Microsoft Cognitive Toolkit vs Tensorpack

OverviewComparisonAlternatives

Overview

Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit
Stacks18
Followers21
Votes0
GitHub Stars17.2K
Forks4.4K
Tensorpack
Tensorpack
Stacks1
Followers7
Votes0
GitHub Stars6.3K
Forks1.8K

Microsoft Cognitive Toolkit vs Tensorpack: What are the differences?

What is Microsoft Cognitive Toolkit? An open-source toolkit for deep learning. It is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph.

What is Tensorpack? A neural network training interface based on TensorFlow. It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.

Microsoft Cognitive Toolkit and Tensorpack can be primarily classified as "Machine Learning" tools.

Some of the features offered by Microsoft Cognitive Toolkit are:

  • Speed & Scalability
  • Commercial-Grade Quality
  • Easy-to-use architecture

On the other hand, Tensorpack provides the following key features:

  • Training interface based on TensorFlow
  • Focus on training speed
  • Focus on large datasets

Microsoft Cognitive Toolkit and Tensorpack are both open source tools. Microsoft Cognitive Toolkit with 16.7K GitHub stars and 4.41K forks on GitHub appears to be more popular than Tensorpack with 5.36K GitHub stars and 1.64K GitHub forks.

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Detailed Comparison

Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit
Tensorpack
Tensorpack

It is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph.

It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.

Speed & Scalability; Commercial-Grade Quality; Easy-to-use architecture
Training interface based on TensorFlow; Focus on training speed; Focus on large datasets
Statistics
GitHub Stars
17.2K
GitHub Stars
6.3K
GitHub Forks
4.4K
GitHub Forks
1.8K
Stacks
18
Stacks
1
Followers
21
Followers
7
Votes
0
Votes
0
Integrations
C++
C++
Python
Python
Python
Python
TensorFlow
TensorFlow

What are some alternatives to Microsoft Cognitive Toolkit, Tensorpack?

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

Polyaxon

Polyaxon

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

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.

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