• LOGIN
  • No products in the cart.

Login

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

Course Reviews

N.A

ratings
  • 5 stars0
  • 4 stars0
  • 3 stars0
  • 2 stars0
  • 1 stars0

No Reviews found for this course.

5688 STUDENTS ENROLLED
© Copyright - Data Science Dojo