Machine Learning Crash Course With ML.NET
We will go over what machine learning is, what it can be used for and we will create a model using C# & ML.NET
Jon Wood YouTube Channel:
http://youtube.com/c/JonWood
Code:
https://github.com/jwood803/MLNet_CrashCourse/blob/master/MLNetCrashCourse/Program.cs
Data:
https://www.kaggle.com/camnugent/california-housing-prices
ML.NET:
https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet
Timestamps:
00:00 - Intro
00:20 - What is Machine Learning?
01:05 - Types of Machine Learning Systems
01:55 - Supervised Learning
02:36 - Unsupervised Learning
03:17 - The Machine Learning Process
05:26 - What is ML.NET?
05:42 - Benefits of ML.NET
08:01 - ML.NET Model Builder
07:49 - ML.NET Demo: The data
08:53 - ML.NET Demo: Installing ML.NET
09:37 - ML.NET Demo: Creating the ML Context
09:48 - ML.NET Demo: Loading in the data
11:47 - ML.NET Demo: Splitting the data
12:47 - ML.NET Demo: Extract Features
13:53 - ML.NET Demo: Building the Pipeline
15:43 - ML.NET Demo: Create Model and Make Test Predictions
16:21 - ML.NET Demo: Evaluate the Model
17:03 - ML.NET Demo: Running the Program
17:36 - ML.NET Model Builder Demo
20:44 - Conclusion
Watch on YouTube ↗
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Chapters (21)
Intro
0:20
What is Machine Learning?
1:05
Types of Machine Learning Systems
1:55
Supervised Learning
2:36
Unsupervised Learning
3:17
The Machine Learning Process
5:26
What is ML.NET?
5:42
Benefits of ML.NET
8:01
ML.NET Model Builder
7:49
ML.NET Demo: The data
8:53
ML.NET Demo: Installing ML.NET
9:37
ML.NET Demo: Creating the ML Context
9:48
ML.NET Demo: Loading in the data
11:47
ML.NET Demo: Splitting the data
12:47
ML.NET Demo: Extract Features
13:53
ML.NET Demo: Building the Pipeline
15:43
ML.NET Demo: Create Model and Make Test Predictions
16:21
ML.NET Demo: Evaluate the Model
17:03
ML.NET Demo: Running the Program
17:36
ML.NET Model Builder Demo
20:44
Conclusion
🎓
Tutor Explanation
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