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  5. .NET for Apache Spark vs Microsoft Cognitive Toolkit

.NET for Apache Spark vs Microsoft Cognitive Toolkit

OverviewComparisonAlternatives

Overview

Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit
Stacks18
Followers21
Votes0
GitHub Stars17.2K
Forks4.4K
.NET for Apache Spark
.NET for Apache Spark
Stacks31
Followers46
Votes0
GitHub Stars2.1K
Forks329

.NET for Apache Spark vs Microsoft Cognitive Toolkit: What are the differences?

Developers describe .NET for Apache Spark as "Makes Apache Spark™ Easily Accessible to .NET Developers". With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. On the other hand, Microsoft Cognitive Toolkit is detailed as "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.

.NET for Apache Spark and Microsoft Cognitive Toolkit belong to "Machine Learning Tools" category of the tech stack.

.NET for Apache Spark and Microsoft Cognitive Toolkit are both open source tools. It seems that Microsoft Cognitive Toolkit with 16.3K GitHub stars and 4.34K forks on GitHub has more adoption than .NET for Apache Spark with 1.16K GitHub stars and 119 GitHub forks.

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Detailed Comparison

Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit
.NET for Apache Spark
.NET for Apache Spark

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.

With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data.

Speed & Scalability; Commercial-Grade Quality; Easy-to-use architecture
-
Statistics
GitHub Stars
17.2K
GitHub Stars
2.1K
GitHub Forks
4.4K
GitHub Forks
329
Stacks
18
Stacks
31
Followers
21
Followers
46
Votes
0
Votes
0
Integrations
C++
C++
Python
Python
Apache Spark
Apache Spark
.NET
.NET
F#
F#
C#
C#
Ubuntu
Ubuntu

What are some alternatives to Microsoft Cognitive Toolkit, .NET for Apache Spark?

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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