Companies can now hire .NET developers remotely with Turing. Hire now and spin up your dream engineering team with Turing's Intelligent Talent Cloud that uses AI to source, vet, match, and manage 1.5 million developers worldwide.

All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.

Role requiring'No experience data provided' months of experience in None We are looking for C#/.net developers on mid and senior levels to join the Software engineering teams If you're interested in finding out more about this fantastic opportunity please get your application in and we can arrange a call. Role requiring'No experience data provided' months of experience in None Junior C# developer to join our team. You will be the main developer working on an Excel Addin that uses a SQLite backend. We make incremental changes and new features for our customer base. The application is reasonably complex, there will be lots of learn for a junior programmer.

Role requiring'No experience data provided' months of experience in None Contact only through Upwork and any other attempt will disqualify the candidate. Israel Fintech Company is looking for an ASP.NET developer full-time. We are in the market for 11 years, growing all the time, and now trying to expand the business to the USA and CAD. Our working schedule is from Monday to Friday (9:00 – 18:00) in GMT 3. Must be able to communicate in English by type and by voice. A good candidate must be smart, ready for self-development, obligatory, and punctual.

Our mission is to make sure that they don't have to leave that behind when reaching for opportunities in Data Science Machine Learning and AI. The well established Python based Machine Learning ecosystem is not quite accessible to millions of .NET developers. We are effectively changing that.

Last month, Microsoft released the first major version of .NET for Apache Spark, an open-source package that brings .NET development to the Apache Spark platform. The new release allows .NET developers to write Apache Spark applications using .NET user-defined functions, Spark SQL, and additional libraries such as Microsoft Hyperspace and ML.NET. Apache Spark is an open-source, general-purpose analytics engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning, and graph processing. Initially developed by the AMPLab team at UC Berkeley, it can be used in conjunction with different data repositories, including the Hadoop Distributed File System, NoSQL databases, and relational data stores. Since all data is processed in-memory (RAM), Spark can be 100x faster than Hadoop for large-scale data processing.

In April 2019 our partner Schneider Electric launched EcoStruxure Workplace Advisor, a smart building application aiming to increase the efficiency of managed office facilities. In this posting I want to outline the general architecture of this application which is based on Trinity RDF: our enterprise .NET API which enables developers without RDF experience to build knowledge graph applications. For anyone interested in increasing the productivity and flexibility of knowledge graph development teams I would like to advertise my talk on Tuesday where I will share more details about the case. The industry use case I will be presenting is Schneider Electric's EcoStruxure Workplace Advisor. Using this service one can derive actionable insights about a building through intuitive dashboards that analyse and integrate data from numerable IoT sensors and systems.

Join Zeeshan Siddiqui talk about all the exciting work which has been going into our open source ML.NET library. We just had a release (1.2.0!). The team are presenting a paper in KDD this August which talks about some of the impressive technical achievements in ML.NET. Zeeshan is going to talk us through this paper step by step. Some of the headline talking points are how we can achieve 3 orders of magnitude improvement in training time with ML.NET compared to SK-learn!

Today, coinciding with //BUILD 2019/ conference, we're thrilled by launching ML.NET 1.0 release! You can read the official ML.NET 1.0 release announcement Blog Post here and get started at the ML.NET site here. In this blog post I'm providing quite a few additional technical details along with my personal vision that you might find interesting, though. This is the first main milestone of a great journey in the open that started on May 2018 when we released ML.NET 0.1 as open source. Since then we've been releasing monthly, 12 preview releases plus this final 1.0 release, as shown in the roadmap below: The diagram above shows the the development in the open of ML.NET, however, as explained below, ML.NET has been internally used by Microsoft for quite a few years and used by other Microsoft products such as Bing Ads, Office, Windows, Azure, etc. ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS), created by Microsoft, for .NET developers.

Automated machine learning has been drawing lots of attention lately, and is software that automatically selects and trains ML models. Some think it replaces the job of a data scientist however there are limitations as to what it can do. Presently, Microsoft's AutoML is able to build a set of ML models automatically, intelligently select models for training, then recommend the best one for you based on the ML problem and data type. Typically a data scientist with their domain expertise would manually produce and compare dozens of models. In a nutshell, it selects the right algorithm and helps to tune hyperparameters.