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Cancer Mass Classifier: Harnessing Machine Learning
Mammoth Interactive Courses Introduction
Preface
00 About Mammoth Interactive (1:12)
01 How To Learn Online Effectively (13:46)
Source Files
Preprocess a malignant vs benign cancer mass dataset
Project Preview (2:22)
Load And Analyze Cancer Dataset (5:46)
Preprocess Cancer Data For Machine Learning (5:24)
Source files
Build an SVM model to classify malignant vs benign cancer mass
Why Do We Need Svm (7:15)
How Does Svm Work (6:28)
Svm On Non-Linear Data (4:48)
What Are Svm Kernels (4:44)
What Is The Precision-Recall Score (4:42)
Build An Svm Model To Classify Malignant Vs Benign Mass (4:08)
Source Files
Build a logistic regression model to classify malignant vs benign cancer mass
What Is Logistic Regression (4:32)
Build A Logistic Regression Model (3:44)
Source files
Improve model accuracy with tuning methods
What Is Cross Validation (8:25)
Find Model Error With Cross Validation (3:46)
What Is Grid Search Cross Validation (5:47)
Find Optimal Hyperparameters With Grid Search (9:37)
What Is Nested Cross Validation (14:29)
Find Best Model Parameters With Nested Cross Validation (4:43)
What Is The Decision Tree Model (10:51)
Compare Models With Nested Cross Validation (4:00)
Source Files
What Are Svm Kernels
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