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Azure Machine Learning Development: Part 1

سرفصل های دوره

Machine learning as a concept has been around for over 60 years, but as artificial intelligence becomes more and more popular, there’s increased opportunity in the field of artificial intelligence and its subgroups, machine learning and deep learning. And with the explosion of cloud computing, it’s only natural to study machine learning with cloud technologies like Azure. In this introductory course to her Azure machine learning series, Zarina Meeran starts you off with the basics of AI, and covers how ML and DL subgroups fit into the picture. She then dives into the various machine learning problems and the machine learning algorithms used to solve these problems. Zarina also covers the machine learning lifecycle to get the end-to-end picture, as well as the tools offered from Azure. Finally, she goes through the architecture of MLOps within the cloud as this is currently adopted.

  • 01.01-importance of azure machine learning development
  • 02.01-what is artificial intelligence (ai)
  • 02.02-benefits of ai
  • 03.01-what is machine learning (ml)
  • 03.02-ml problem types
  • 03.03-supervised learning
  • 03.04-unsupervised learning
  • 03.05-semisupervised learning
  • 03.06-reinforcement learning
  • 04.01-what is deep learning (dl)
  • 04.02-ml vs. dl
  • 05.01-clustering
  • 05.02-classification
  • 05.03-regression
  • 05.04-anomaly detection
  • 06.01-ml lifecycle
  • 06.02-azure ml tools
  • 07.01-what is mlops
  • 07.02-mlops team roles
  • 08.01-next steps
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