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.NET for Apache Spark

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Theano

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.NET for Apache Spark vs Theano: 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, Theano is detailed as "Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently". Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme.

.NET for Apache Spark and Theano can be categorized as "Machine Learning" tools.

.NET for Apache Spark and Theano are both open source tools. It seems that Theano with 8.83K GitHub stars and 2.49K forks on GitHub has more adoption than .NET for Apache Spark with 1.11K GitHub stars and 108 GitHub forks.

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What is .NET for Apache Spark?

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.

What is Theano?

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).

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What companies use Theano?
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What tools integrate with .NET for Apache Spark?
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What are some alternatives to .NET for Apache Spark and Theano?
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.
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/
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
See all alternatives