PeachPie is a modern PHP compiler based on the Microsoft Roslyn compiler platform and drawing from our popular Phalanger project. It allows PHP to be executed within the .NET framework, thereby opening the door for PHP developers into the world of .NET – and vice versa. The project allows for hybrid applications, where parts are written in C# and others in PHP. The parts will be entirely compatible and can communicate seamlessly, all within the .NET framework.

PeachPie - The open-source PHP compiler to .NET

Excelize is a library written in pure Go providing a set of functions that allow you to write to and read from XLSX / XLSM / XLTM / XLTX files. Supports reading and writing spreadsheet documents generated by Microsoft Excel™ 2007 and later. Supports complex components by high compatibility, and provided streaming API for generating or reading data from a worksheet with huge amounts of data.
 
With Excelize chart generation and management is as easy as a few lines of code. You can build charts based off data in your worksheet or generate charts without any data in your worksheet at all.

Excelize is a library written in pure Go providing a set of functions that allow you to write to and read from XLSX / XLSM / XLTM / XLTX files. Supports reading and writing spreadsheet documents generated by Microsoft Excel™ 2007 and later. Supports complex components by high compatibility, and provided streaming API for generating or reading data from a worksheet with huge amounts of data

Excelize - Golang library for reading and writing Microsoft Excel (XLSX) files

The Microsoft Cognitive Toolkit is a free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. It is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. 
 
In this directed graph, leaf nodes represent input values or network parameters, while other nodes represent matrix operations upon their inputs. CNTK allows to easily realize and combine popular model types such as feed-forward DNNs, convolutional nets (CNNs), and recurrent networks (RNNs/LSTMs).
 
CNTK can be included as a library in your Python or C++ programs, or used as a standalone machine learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your C# or Java program.

The Microsoft Cognitive Toolkit is a free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. It is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. 


CNTK - Computational Network Toolkit (CNTK)

OneFuzz framework, an open source developer tool to find and fix bugs at scale. Fuzz testing is a highly effective method for increasing the security and reliability of native code—it is the gold standard for finding and removing costly, exploitable security flaws. Traditionally, fuzz testing has been a double-edged sword for developers: mandated by the software-development lifecycle, highly effective in finding actionable flaws, yet very complicated to harness, execute, and extract information from.  

OneFuzz - A self-hosted Fuzzing-As-A-Service platform

MMLSpark provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.MMLSpark requires Scala 2.11, Spark 2.1+, and either Python 2.7 or Python 3.5+. See the API documentation for Scala and for PySpark.
 
Its features include : 
<ul>
<li>Easily ingest images from HDFS into Spark </li>
<li>Pre-process image data using transforms from OpenCV </li>
<li>Featurize images using pre-trained deep neural nets using CNTK </li>
<li> Use pre-trained bidirectional LSTMs from Keras for medical entity extraction</li>
<li>Train DNN-based image classification models on N-Series GPU VMs on Azure</li>
<li>Train classification and regression models easily via implicit featurization of data </li>
<li>Compute a rich set of evaluation metrics including per-instance metrics</li>
</ul>

MMLSpark provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.MMLSpark requires Scala 2.11, Spark 2.1+, and either Python 2.7 or Python 3.5+. See the API documentation for Scala and for PySpark.

MMLSpark - Microsoft Machine Learning for Apache Spark

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PeachPie - The open-source PHP compiler to .NET

Excelize - Golang library for reading and writing Microsoft Excel (XLSX) files

CNTK - Computational Network Toolkit (CNTK)

OneFuzz - A self-hosted Fuzzing-As-A-Service platform

MMLSpark - Microsoft Machine Learning for Apache Spark

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PeachPie - The open-source PHP compiler to .NET

Excelize - Golang library for reading and writing Microsoft Excel (XLSX) files

CNTK - Computational Network Toolkit (CNTK)

OneFuzz - A self-hosted Fuzzing-As-A-Service platform

MMLSpark - Microsoft Machine Learning for Apache Spark

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