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A first-hand look from the .NET engineering teams

This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. This is the first machine learning textbook to include a comprehensive coverage of recent developments such as probabilistic graphical models and deterministic inference methods, and to emphasize a modern Bayesian perspective. It is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. This hard cover book has 738 pages in full colour, and there are 431 graded exercises (with solutions available below). Extensive support is provided for course instructors.

We’re excited to announce today the release of ML.NET 0.7 – the latest release of the cross-platform and open source machine learning framework for .NET developers (ML.NET 0.1 was released at //Build 2018). This release focuses on enabling better support for recommendation based ML tasks, enabling anomaly detection, enhancing the customizability of the machine learning pipelines, enabling using ML.NET in x86 apps, and more.

ML.NET is a free, cross-platform, and open source machine learning framework for .NET developers. It is also an extensible platform that powers Microsoft ser...

Microsoft open-sources Infer.NET, an AI engine that helps power Azure cloud services - SiliconANGLE

“This is no ordinary cat video. 🐈This one explains #quantumcomputing in less than 4 minutes. Watch meow: https://t.co/si7U1rbH5H”

Introduction - 0:00 Overview Machine Learning in Oracle - 1:31 Machine Learning theory - 6:04 Demonstration: preparation and building the model - 11:52 Demon...

There is no way to predict which quantum system will garner system share in the next years, but most large chip, system, and software companies are

We are excited to share that Video Indexer has a new capability, Spoken Language Identification (LID)!

Microsoft is teaming up with National Geographic to launch the AI for Earth Innovation Grant, an initiative that’ll provide researchers access to AI development tools.