Azure Machine Learning Development: Part 1
1h 8mIntermediate2022-08-22
Authors
Zarina Meeran
Senior Cloud System Developer at Cloudreach | Azure, GCP, CCNA
Course details
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.
Skills covered
Cloud DevelopmentMachine LearningPersonaAzureArtificial Intelligence (AI)Cloud ComputingMicrosoft
Concepts
Introduction
- Importance of Azure Machine Learning development
Artificial Intelligence (AI)
- What is artificial intelligence (AI)
- Benefits of AI
Machine Learning (ML)
- What is machine learning (ML)
- ML problem types
- Supervised learning
- Unsupervised learning
- Semisupervised learning
- Reinforcement learning
Machine Learning (ML) and Deep Learning (DL)
- What is deep learning (DL)
- ML vs. DL
Machine Learning Algorithms
- Clustering
- Classification
- Regression
- Anomaly detection
Machine Learning Lifecycle and Azure Machine Learning
- ML lifecycle
- Azure ML tools
Machine Learning Operations (MLOps)
- What is MLOps
- MLOps team roles
Conclusion
- Next steps