Course Curriculum
Welcome | |||
Learning Objectives | 00:00:00 | ||
Introduction | |||
Agenda | 00:03:00 | ||
Agenda–cont | 00:04:00 | ||
Limitations Of Accuracy | 00:04:00 | ||
Precision and Recall | |||
Confusion Matrix | 00:03:00 | ||
Measuring Precision | 00:05:00 | ||
Introduction To Recall (Sensitivity) | 00:04:00 | ||
Measuring Recall | 00:04:00 | ||
Precision vs Recall | 00:05:00 | ||
Precision Example | 00:06:00 | ||
Building A Model | 00:10:00 | ||
F1 Score | 00:02:00 | ||
Model Pitfalls | |||
Judging Model Accuracy | 00:03:00 | ||
Generalizations And Overfitting | 00:05:00 | ||
Model Training | |||
Train/ Test Partitioning | 00:11:00 | ||
Public Private Leaderboard | 00:11:00 | ||
Bias and Variance | |||
Introduction | 00:05:00 | ||
Model Complexity | 00:08:00 | ||
Goldilocks Dilemma | 00:02:00 | ||
The Objective | 00:02:00 | ||
Creating Random Samples Of Test Data | 00:05:00 | ||
Effects On Models | 00:06:00 | ||
Evaluating The Trade-off | 00:07:00 | ||
Choosing A Model | 00:06:00 | ||
Cross Validation | |||
Methods Of Evaluation | 00:07:00 | ||
Adjusting Learning Parameters P1 | 00:08:00 | ||
Adjusting Learning Parameters P2 | 00:10:00 | ||
Model Evaluation Quiz | |||
Model Evaluation | 00:10:00 | ||
Deliberate Practice | |||
Exercise: Detecting Kyphosis in Kids Using Decision Tree Model | 01:00:00 | ||
Supplemental Exercises | |||
Exercise : Classifying Iris Dataset with a Decision Tree Model | 00:45:00 | ||
Exercise(Python):Detecting Kyphosis in Kids Using Decision Tree Model | 00:45:00 | ||
Resources | |||
Evaluation Resources | 00:05:00 |
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