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Introduction to Machine Learning (CUX102)


Description
This course is a general introduction to the field of machine learning, designed for all disciplines. It goes over machine learning concepts at a high level, and introduces key terms and concepts that you will encounter on any project involving machine learning. We recommend taking this course if you are unfamiliar with machine learning and are starting on a project that involves working with machine learning models and/or building conversational experiences. This course is open to all disciplines and does not require programming experience.
Content
  • Welcome
  • 1. The Basics
  • 1.1. Core Concept
  • 1.2. Types of Machine Learning
  • 1.3. Types of Models
  • Quiz #1
  • 2. Machine Learning and Data
  • 2.1. Machine Learning and Data
  • 2.2. Input Data in ML
  • 2.3. Types of Results
  • Quiz #2
  • 3. Evaluating and Improving Your Model
  • 3.1. Measuring Performance
  • 3.2. Classification Performance
  • 3.3. Regression Performance
  • 3.4. Clustering Performance
  • 3.5. Common Issues
  • Quiz #3
  • 4. Wrapping Up
  • Common Misconceptions
  • The End
  • Course Feedback
Completion rules
  • You must complete the units "1.1. Core Concept, 1.2. Types of Machine Learning, 1.3. Types of Models, Quiz #1, 2.1. Machine Learning and Data, 2.2. Input Data in ML, 2.3. Types of Results, Quiz #2, 3.1. Measuring Performance, 3.2. Classification Performance, 3.3. Regression Performance, 3.4. Clustering Performance, 3.5. Common Issues, Quiz #3, Common Misconceptions"
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