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  • Online

Microsoft Azure: AI-in-a-Day

Type:

  • Virtual Training

Topic(s):

  • Azure
  • ML
Register

With growing volumes of data and a wider collection of sources than ever before, Artificial Intelligence (AI) is becoming a key part of how we process data to understand what’s happening in the business. Microsoft Azure presents tools for every user, addressing a range of use cases from drag-and-drop forecasting to automated classification or pre-trained models for understanding free text like customer feedback or images such as products coming off the production line.

Join us on September 30th, 10am – 4pm and take advantage of our one-day, hands-on introduction to the Azure Machine Learning Studio, where you can drag-and-drop in Designer to create models, use Automated Machine Learning to find the best from hundreds of potential models, or use Notebooks to write custom R and Python code to build models tailored to even the most specific use cases. We’ll also look at Cognitive Services, bringing Microsoft’s cutting-edge models for language understanding, image recognition and more, to extract useful insights from your unstructured data, with the minimum effort.

Keeping your business’s needs at the forefront, we will:

  • Present a blueprint for building statistical models and discuss some key best practices in advanced analytics projects
  • Introduce the different tools in Azure ML – Auto ML, Designer, and Notebooks that can be used to prepare machine learning models
  • Showcase Cognitive Services, and how you can make use of Microsoft’s leading pre-built models to extract insight from text, images, and more
  • Explore the offerings in Azure ML through hands-on examples, supported by Thorogood consultants

Is it for you?

  • Would you like to see what Machine Learning and AI options are available in Azure ML?
  • Are you looking for hands-on experience to get started and increase your familiarity with AI in Azure?
  • Do you want to understand how Data Science skills could unlock opportunities to get more valuable insights from your data?