Applied Machine Learning Quiz

What is the time allocated for the Case study on APGAR score?

Which activity has the longest allocated time?

According to the Oxford English Dictionary, what is the definition of learning in the context of psychology?

Which of the following is NOT listed as an application of Machine Learning?

Where is the application of Spam detection mentioned in the context of Machine Learning?

What is the time allocated for the Discussion activity?

Which activity has the same allocated time as the Challenge activity?

In the Machine Learning context, which application is NOT mentioned?

What is the total time allocated for the activities related to Analysis?

Where is the application of Customer segmentation mentioned in the context of Machine Learning?

Course Overview

Machine Learning course (18-785) led by Patrick McSharry at Carnegie Mellon University.
Focuses on applying machine learning techniques to large real-world datasets for knowledge discovery, predictive analytics, and decision support.

Learning Objectives

Develop expertise in machine learning methodologies and their applications.
Introduce and demonstrate techniques for data refining, visualization, exploration, and modeling.
Analyze advantages and disadvantages of various machine learning methods including linear, nonlinear, nonparametric, and ensemble approaches.
Address challenges in both supervised and unsupervised learning contexts.

Textbooks

The Elements of Statistical Learning by T. Hastie, R. Tibshirani, and J. Friedman (Springer-Verlag, 2001).
Pattern Recognition and Machine Learning by Christopher Bishop (Springer, 2006).

Weekly Course Outline

Week 7: Statistical learning.
Week 8: Linear models.
Week 9: Nonlinear models.
Week 10: Supervised learning.
Week 11: Unsupervised learning.
Week 12: Ensemble approaches.

Instructor Contact Information

Patrick McSharry
Email: [email protected]
Website: www.mcsharry.net
Twitter: @patrickmcsharry
Course occurs in Fall 2023 at ICT Center of Excellence.

Important Concepts

Statistical learning encompasses both traditional statistical methods and modern machine learning techniques.
Understanding different modeling approaches is crucial for effective application of machine learning in varied contexts.

Test your knowledge of machine learning techniques and their application to real-world datasets with this quiz. Covering topics from the Data, Inference & Applied Machine Learning Course by Patrick McSharry, the quiz will challenge your understanding of applied machine learning concepts.