Introduction to Machine Learning with Azure

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What Will You Learn?

Gain a high-level introduction to the field of machine learning and prepare to use Azure Machine Learning Studio to train machine learning models. Plus, learn how to perform a variety of tasks on Azure Machine Learning labs — from data import, transformation and management to training, validating and evaluating models. Access to the Azure Machine Learning Labs will close after a predetermined number of students have completed the course.

About This Course

Provider: Udacity
Format: Online
Duration: 22 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: After completing this free course, you'll be able to get solid foundation of machine learning with Azure
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: Microsoft
Key Topics: Machine Learning, Azure Machine Learning Studio, Artificial intelligence
Topic Covered: 
  2. - What is Machine Learning?
  3. - Applications of Machine Learning
  4. - The Data Science Process
  5. - Common Types of Data
  6. - Tabular Data
  7. - Scaling Data
  8. - Encoding Categorical Data
  9. - Image Data
  10. - Text Data
  11. - Two Perspectives on ML
  12. - The Computer Science Perspective
  13. - The Statistical Perspective
  14. - The Tools for Machine Learning
  15. - Libraries
  16. - Cloud Services
  17. - Models vs. Algorithms
  18. - Linear Regression
  19. - Azure ML Service
  20. - Parametric vs. Non-parametric
  21. - Classical ML vs. Deep Learning
  22. - Approaches to Machine Learning
  23. - Data Import and Transformation
  24. - Walkthrough: Import, Transform, and Export Data
  25. - Managing Data
  26. - Feature Engineering
  27. - Data Drift
  28. - Model Training in Azure Machine Learning
  29. - Confusion Matrices
  30. - Supervised Learning: Classification
  31. - Multi-Class Algorithms
  32. - Supervised Learning: Regression
  33. - Unsupervised Learning
  34. - Clustering
  35. - Classical ML vs. Deep Learning
  36. - What is Deep Learning?
  37. - Benefits and Applications of Deep Learning
  38. - Anomaly Detection
  39. - Forecasting
  40. - Managed Services for Machine Learning
  41. - Modern AI: Challenges and Principles
  42. - Microsoft AI Principles

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Machine Learning Course Machine Learning Free Course Top Free Course Data Science Course Data Sciences Free Course Top Machine Learning Course Machine Learning Foundation