In this post, I'll give a short explanation of neuron, a Visual Studio Code extension that aims to be a one-stop-shop for data scientists. It's an extension I developed as part of a team of students at Imperial College London, in collaboration with Microsoft, in the summer of 2018. Data science is the buzz-word of the 21st century. From IoT devices generating thousands of data points per day, to social media connecting people's information on a scale never seen before, a lot of the development that goes on today sooner or later comes into contact with "data science". Data scientists come from various different technical backgrounds, but the vast majority of them use a standard set of tools of the trade: Python, insert name of trending machine-learning library, and Jupyter Notebooks.

See how you can connect devices to create powerful IoT applications on the flexible Azure IoT platform. See how Azure IoT simplifies IoT development--use your preferred language, tools and existing developer SDKs to start building IoT right away. Get started quickly with solution accelerators such as Remote Monitoring, Predictive Maintenance and Connected Factory for common IoT scenarios. Learn how to use Azure IoT Hub to easily create, customize, and manage all aspects of your IoT application, and IoT Edge to deploy cloud apps on the edge--creating more intelligent solutions, whether in the cloud or on-premises. Create visualizations of IoT time-series data and create insights from your IoT application with other Azure platform services.

My name is Zurab Murvanidze, I am 1st year computer science student at UCL. I love learning about technology and have deep interest in machine learning, data science, quantum computing and artificial intelligence. I like developing applications and games in my spare time and in this article would love to share my experience in ML.NET. This article will cover basics of machine learning, will introduce you to ML.NET and teach you how to create and train machine learning models. It will also demonstrate how can we implement machine learning in ASP.NET Core Web Application.

In my spare time, I love learning new technologies and going to hackathons. Our hackathon project Pantrylogs using Artificial Intelligence was selected as one of the 10 Microsoft Imagine Cup UK finalists. I'm interested in learning more about AI, Data Science, and Machine Learning to improve the performances of our application. In this article, I would love to share my experience of using Azure Machine Learning Studio with you. Azure Machine Learning Studio is a very powerful browser-based, visual drag-and-drop authoring environment.

Mastery of the productivity applications broadly used in business. Microsoft Imagine Academy curricula is organised along learning paths that guide students and educators to earning industry-recognised certifications and skills needed for jobs of tomorrow.

Learn the fundamentals of Microsoft's Machine Learning and Artificial Intelligence services and how to build applications using them. Develop practical job skills that you can start using straight away. Courses provided free in partnership with Pluralsight. Overview Using Microsoft Cognitive Services in your applications Let's begin with this short video that explains the Microsoft Cognitive Services and shows a sample application. Explain to a friend what Cognitive Services are and give an example of how you can use them in an application. Introduction and Setup Install and configure Visual Studio To get started, you'll need Visual Studio to create and run your Cognitive Services application. Open Visual Studio and create a simple application.

Artificial Intelligence (AI) is proving to be a massively disruptive force, one that is leading to the digital transformation of businesses at a faster pace than most of us would have imagined. This curriculum is primarily oriented towards these two personas which meet the demands of Undergraduate and Postgraduate students. The target profile here is developer who is yet to use Microsoft AI tools and APIs to infuse intelligence into their applications. This profile relates to developers and data scientists who currently build AI and machine learning solutions and want to know how to do this with Microsoft's tools, framework and processes, such as the Azure Machine Learning Workbench and the Team Data Science Process. Services covered include, Cognitive Services and Azure Bot Services.

LUIS is now generally available in the Australia East, Brazil South, West US 2, South Central US, East US, East Asia, and North Europe regions, in addition to the current availability in the East US 2, West Central US, West US, West Europe, and Southeast Asia regions. General availability (GA) pricing will begin on February 1, 2018. Usage prior to February 1, 2018, will be billed at preview rates.

ND-Series VMs are available in the West US 2, East US, West Europe, and Southeast Asia regions. NCv2-Series VMs are available the West US 2 and East US regions and will be available later in December 2017 in West Europe and South Central US. NCv3-Series VMs are available for early customer access. To sign up for the preview, please complete the Access to Azure Next Generation GPU VMs online form.

Visual Studio Code Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions in Microsoft Visual Studio Code. This extension seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people. VS Code Tools for AI is a cross-platform extension that supports deep learning frameworks including Microsoft Cognitive Toolkit (CNTK), Google TensorFlow and more.