stream:// data science
Announcing ML.NET 0.10 – Machine Learning for .NET
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models. ML.NET allows you to create and use machine learning models targeting common tasks such as classification, regression, clustering, ranking, recommendations and anomaly detection. It also supports the broader open source ecosystem by proving integration with popular deep-learning frameworks like TensorFlow and interoperability through ONNX. Some common use cases of ML.NET are scenarios like Sentiment Analysis, Recommendations, Image Classification, Sales Forecast, etc. Please see our samples for more scenarios.
Getting started with FsLab - FsLab
FsLab is a curated collection of open source F# packages for data-science. Together with your editor or Jupyter notebook these packages allow you to rapidly develop scalable, high-performance analytics and visualizations using succinct, type-safe, production-ready code. Download
GitHub: The top 10 programming languages for machine learning
Online code repository GitHub has pulled together the 10 most popular programming languages used for machine learning hosted on its service, and, while Python tops the list, there's a few surprises.
Announcing ML.NET 0.9 – Machine Learning for .NET
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models.
Machine Learning in NET (ML NET) full tutorial
Machine Learning in NET (ML NET) full tutorial
A Year of Q#
The Quantum Architecture and Computation group launched Q#, our quantum computing programming language, a year ago on December 11th, 2017. Q# 0.1 was the result of a lot of hard work from a small, dedicated team of developers, researchers, and program managers. We had made the decision to build a domain-specific language for quantum computing about six months before we launched, so we were on a very tight schedule. We were lucky to have a great team of people who all pitched in and did what needed to be done so that we could meet our extremely aggressive timetable.
Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI
Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI KDnuggets Subscribe to KDnuggets News | &
Microsoft Puts More Brain-Power Into Machine Learning For Azure Cloud
Computer brains need models that can be exposed to datasets, trained, tested and enriched over time as they learn what’s right, what’s wrong and ultimately what is altogether culturally and ethically appropriate or not.
Announcing ML.NET 0.8 – Machine Learning for .NET
A first-hand look from the .NET engineering teams
Christopher Bishop at Microsoft Research
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.
Announcing ML.NET 0.7 (Machine Learning .NET)
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.
Machine learning with ML.NET - BRK3196
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
Microsoft open-sources Infer.NET, an AI engine that helps power Azure cloud services - SiliconANGLE
Microsoft on Twitter
“This is no ordinary cat video. 🐈This one explains #quantumcomputing in less than 4 minutes. Watch meow: https://t.co/si7U1rbH5H”
Machine Learning with Oracle
Introduction - 0:00 Overview Machine Learning in Oracle - 1:31 Machine Learning theory - 6:04 Demonstration: preparation and building the model - 11:52 Demon...
Microsoft Builds Quantum Strategy Around Q#
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
Spoken Language Identification in Video Indexer | Блог | Microsoft Azure
We are excited to share that Video Indexer has a new capability, Spoken Language Identification (LID)!
Microsoft’s AI for Earth Innovation Grant gives data scientists access to AI tools
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.
The most important unanswered questions of 2018 in Artificial Intelligence (AI) and Machine Learning (ML) - Dataconomy
Here is what a recent whitepaper by Dataiku reveals about Artificial intelligence and machine learning emphasising on the role of data scientists. Let’s find out. (This is the first part of an article series based on a whitepaper by Dataiku) The year 2018 was supposed to be the one
Machine Learning with ML.NET – Solving Real-World Classification Problem (Wine Quality) | Rubik's Code
Code that accompanies this article can be downloaded here. In the first article of machine learning in ML.NET saga, we explored basics of machine learning and we got our first look at Microsoft’s…
The animated guide to artificial intelligence (Explanimators: Episode 1)
An easy guide to everything AI. More from Microsoft Story Labs: microsoft.com/storylabs. Subscribe to Microsoft on YouTube here: https://aka.ms/SubscribeToYo...
ML.NET 0.2 Adds Clustering, New Examples
Microsoft's ML.NET is a multi-platform machine learning framework that runs on .NET Core. First debuted in May during Build, its second release adds several new features and a separate GitHub repo demonstrating how to put the framework to use.
Demystifying Machine and Deep Learning for Developers : Build 2018
To build the next set of personalized and engaging applications, more and more developers are adding ML to their applications. In this session, you'll learn ...
'NEW SESSION' Introducing ML.NET
ML.NET is aimed at providing a first class experience for Machine Learning in .NET. Using ML.NET, .NET developers can develop and infuse custom AI into exist...
Introducing ML.NET: Cross-platform, Proven and Open Source Machine Learning Framework
Today at //Build 2018, we are excited to announce the preview of ML.NET, a cross-platform, open source machine learning framework. ML.NET will allow .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models.
Hot Vacancies
DevOps Engineer
Our team is urgently looking for a DevOps Engineer for a direct 6-month contract. The client is based in the Netherlands, and the domain is healthcare. The primary task is to assist with the migration from a local data center to Azure.
.NET Developer
A developer is needed for an American startup that manages the operation and maintenance of residential complexes. This is a new project from scratch with a temporary integration of the old system (Web Forms, no code access).
.NET Backend Developer
Field Complete is a team of passionate, young & fun-loving professionals looking to change the uneffective way that Servicing Industry works on US markets. Field Complete is growing really fast. We are looking for a Back End Developer to build a top-level modern API, ready for high load. Strong expertise with:
Senior Xamarin Developer
You will join a mobile team which is working on two very exciting projects, Sportsbook and Casino. The apps are used by users in the US, where we are working on the regulated markets. We are releasing apps every two weeks. Our apps are generating almost 75% of the company revenue and the user base is growing daily. Technical stack on the project: Xamarin.Forms, MVVM with DI, NewRelic, Azure + App Center etc. Switching to .Net MAUI in the nearest 2-3 months.
Senior .NET Engineer
You will be working in a large US-oriented company that puts as a priority: security, performance, and stability. The candidate will work on pushing a huge number of changes (several thousand per sec) to several thousand clients in a near real-time manner.