Yes, there’s the option of building your own specific models using Azure’s Machine Learning studio, working with tools like PyTorch and TensorFlow to design and train models from scratch.

The skill of feature engineering — crafting data features optimized for machine learning — is as old as data science itself. But it’s a skill I’ve noticed is becoming more and more neglected.

Microsoft first launched Machine Learning as a preview in June 2014, though did not state when the service would go live. Early users include the Pier 1 retail chain, Carnegie Mellon University ...

Understand, protect and control your machine learning solution. Over the past several years, machine learning has moved out of research labs and into the mainstream, and has transformed from a niche ...

In fall 2014, the Practice of Machine Learning Conference held at Microsoft crowned Dr. Pig the winner of its first-ever Azure Machine Learning Cloud App Contest. Developed by the Microsoft Lab 1711 – ...

The new interface for Azure’s automated machine learning tool makes creating a model as easy as importing a data set and then telling the service which value to predict. Users don’t need to ...

Microsoft wants companies to build their own AI-powered “copilots” — using tools on Azure and machine learning models from its close partner OpenAI, of course. Microsoft defines a “copilot ...

At its Ignite 2021 virtual conference this week, Microsoft announced updates across Azure Arc, its service that brings Azure products and management to multiple clouds, edge devices, and ...

HCLTech has acquired two new Microsoft Azure specializations for its artificial intelligence (AI) and machine learning (ML) solutions. These new specializations are AI and Machine Learning on ...