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Study mode:
on
1
- Intro
2
- What is Machine Learning?
3
- Types of Machine Learning Systems
4
- Supervised Learning
5
- Unsupervised Learning
6
- The Machine Learning Process
7
- What is ML.NET?
8
- Benefits of ML.NET
9
- ML.NET Model Builder
10
- ML.NET Demo: The data
11
- ML.NET Demo: Installing ML.NET
12
- ML.NET Demo: Creating the ML Context
13
- ML.NET Demo: Loading in the data
14
- ML.NET Demo: Splitting the data
15
- ML.NET Demo: Extract Features
16
- ML.NET Demo: Building the Pipeline
17
- ML.NET Demo: Create Model and Make Test Predictions
18
- ML.NET Demo: Evaluate the Model
19
- ML.NET Demo: Running the Program
20
- ML.NET Model Builder Demo
21
- Conclusion
Description:
Dive into a comprehensive 21-minute video tutorial on machine learning using ML.NET. Explore the fundamentals of machine learning, its various types, and the overall process. Learn about ML.NET, its benefits, and how to use it effectively. Follow along with a hands-on demo that covers data loading, feature extraction, model building, and evaluation using C# and ML.NET. Gain practical insights into supervised and unsupervised learning, and discover how to leverage the ML.NET Model Builder for streamlined development. Access provided code samples and datasets to enhance your learning experience.

Machine Learning Crash Course With ML.NET

Traversy Media
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