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Overview
The “Azure Machine Learning Development: 2 Learning ML Studio” course introduces learners to Microsoft Azure’s ML Studio, a powerful, user-friendly platform for building, training, and deploying machine learning models. Designed for data scientists, developers, and AI practitioners, this course focuses on navigating ML Studio’s environment and utilizing its tools to streamline the machine learning lifecycle. Participants will learn how to create and manage ML experiments, work with datasets, and apply various algorithms and modules for data preprocessing, feature engineering, and...
Syllabus
Introduction
- Importance of Azure Machine Learning development
1. Artificial Intelligence (AI)
- What is artificial intelligence (AI)?
- Benefits of AI
2. Machine Learning (ML)
- What is machine learning (ML)?
- ML problem types
- Supervised learning
- Unsupervised learning
- Semisupervised learning
- Reinforcement learning
3. Machine Learning (ML) and Deep Learning (DL)
- What is deep learning (DL)?
- ML vs. DL
4. Machine Learning Algorithms
- Clustering
- Classification
- Regression
- Anomaly detection
5. Machine Learning Lifecycle and Azure Machine Learning
- ML lifecycle
- Azure ML tools
6. Machine Learning Operations (MLOps)
- What is MLOps?
- MLOps team roles
Conclusion
- Next steps
Instructor
Zarina Meeran
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