Supervised Machine Learning Lectures
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Learning Paths

Learning Paths
ML.NET And C#
The AutoML Tool
Azure Machine Learning
Cognitive Toolkit and C#
Academy Members
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Introduction To Artificial Intelligence

What is Artificial Intelligence?
The History Of AI
Machine Learning
Computer Vision
Natural Language Processing
Bias In Artificial Intelligence
Examples Of Bias In AI
Risks With AI
The Six Principles Of Responsible AI
Recap
Test Your Knowledge
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Prerequisites

Learning Paths
Set Up Visual Studio And The NET SDK
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Loading And Processing Data

Loading And Processing Data
Processing Numeric Data
Handling Outliers
One-Hot Encoding
Binning Geo Data
One-Hot Encoding Geo Bins
Processing Text Data
Recap
Test Your Knowledge
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Data Processing Labs

Learning Paths
Data Processing With ML.NET And C#
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Supervised And Unsupervised Learning

Supervised And Unsupervised Learning
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Regression

Introduction
Linear Patters In Data
The Linear Regression Algorithm
The RMSE Metric
The MAE And MSE Metrics
The Loss Surface
The Gradient Descent Algorithm
Multidimensional Datasets
Multiple Linear Regression
Recap
Test Your Knowledge
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Regression Labs

Learning Paths
Regression With ML.NET And C#
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Binary Classification

Introduction
Binary Patterns In Data
The Threshold Value
The Sigmoid Function
The Confusion Matrix
The Accuracy Metric
The Precision And Recall Metrics
The TPR and FPR Metrics
The ROC Curve
The AUC Metric
The Calibration Curve
Recap
Test Your Knowledge
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Binary Classification Labs

Learning Paths
Binary Classification With ML.NET And C#
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Multiclass Classification

Introduction
Multiclass Classification
One Versus All
One Versus One
The Multiclass Confusion Matrix
Micro And Macro Averages
Recap
Test your knowledge
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Multiclass Classification Labs

Learning Paths
Multiclass Classification With ML.NET And C#
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In Conclusion

Course Recap
Your certificate of completion
Closing Words

The Precision And Recall Metrics

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