University of Colorado Boulder - Classification Analysis
- Offered byCoursera
Classification Analysis at Coursera Overview
Duration | 38 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Classification Analysis at Coursera Highlights
- Earn a certificate of completion
- Add to your LinkedIn profile
- 6 quizzes, 1 assignment
Classification Analysis at Coursera Course details
- What you'll learn
- Understand the concept and significance of classification as a supervised learning method.
- Identify and describe different classifiers, apply each classifier to perform binary and multiclass classification tasks on diverse datasets.
- Evaluate the performance of classifiers, select and fine-tune classifiers based on dataset characteristics and learning requirements.
- The "Classification Analysis" course provides you with a comprehensive understanding of one of the fundamental supervised learning methods, classification. You will explore various classifiers, including KNN, decision tree, support vector machine, naive bayes, and logistic regression, and learn how to evaluate their performance. Through tutorials and engaging case studies, you will gain hands-on experience and practice in applying classification techniques to real-world data analysis tasks.
- By the end of this course, you will be able to:
- 1. Understand the concept and significance of classification as a supervised learning method.
- 2. Identify and describe different classifiers, such as KNN, decision tree, support vector machine, naive bayes, and logistic regression.
- 3. Apply each classifier to perform binary and multiclass classification tasks on diverse datasets.
- 4. Evaluate the performance of classifiers using appropriate metrics, including accuracy, precision, recall, F1 score, and ROC curves.
- 5. Select and fine-tune classifiers based on dataset characteristics and learning requirements.
- Gain practical experience in solving classification problems through guided tutorials and case studies.
Classification Analysis at Coursera Curriculum
Introduction to Classification
Introduction to Classification
Nearest Neighbor Classification
Assessment Strategy
Activity Strategy
Nearest Neighbor Classification Demo
Nearest Neighbor Classification Case Study - Breast Cancer
Nearest Neighbor Classification Case Study
Nearest Neighbor Classification Quiz
Nearest Neighbor Classification Exploration Exercise
Decision Tree Classification
Decision Tree Classification
Decision Tree Classification Demo
Decision Tree Classification Case Study - Breast Cancer
Decision Tree Classification Case Study
Decision Tree Classification Quiz
Decision Tree Classification Exploration Exercise
Support Vector Machine Classification
Support Vector Machine Classification
Support Vector Machine Classification Demo
Support Vector Machine Classification Case Study - Breast Cancer
Support Vector Machine Classification Case Study
Support Vector Machine Classification Quiz
Support Vector Machine Classification Exploration Exercise
Naïve Bayes and Logistic Regression
Naïve Bayes Classification
Logistic Regression Classification
Naïve Bayes Classification Demo
Naïve Bayes Classification Case Study - Breast Cancer
Naïve Bayes Classification Case Study
Logistic Regression Classification Demo
Logistic Regression Classification Case Study - Breast Cancer
Logistic Regression Classification Case Study
Naïve Bayes Classification Quiz
Logistic Regression Classification Quiz
Classification Evaluation
Classification Evaluation
Classification Evaluation Quiz
Case Study
Classification Analysis at Coursera Admission Process
Important Dates
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