IN 404: Machine Learning
Provides a comprehensive study of machine learning algorithms and practical implementations. Covers supervised learning (linear regression, logistic regression, decision trees, random forests, SVM), unsupervised learning (k-means, PCA), model validation…
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Common aliases: IN 404
Study Resources for Machine Learning
Final Exam 2016
Midterm (Exam 1) 2012
Midterm (Exam 2) 2013
Midterm (Exam 1) 2014
Midterm (Exam 1) 2017
Midterm (Exam 1) 2020
Diagnostic Quiz 1
Assessment Inventory for IN 404 (7 Documents)
| Document | Format | Year | Access |
|---|---|---|---|
| Midterm (Exam 1) 2020 | Midterm | 2020 | Illustrative Archive |
| Midterm (Exam 1) 2017 | Midterm | 2017 | Illustrative Archive |
| Final Exam 2016 | Final | 2016 | Illustrative Archive |
| Midterm (Exam 1) 2014 | Midterm | 2014 | Illustrative Archive |
| Midterm (Exam 2) 2013 | Midterm | 2013 | Illustrative Archive |
| Midterm (Exam 1) 2012 | Midterm | 2012 | Illustrative Archive |
| Diagnostic Quiz 1 | Quiz | — | Illustrative Archive |
Complete inventory of all 7 assessments (sorted by most recent). Select any document to inspect or use the search bar above to filter.
Course Overview & Exam Syllabus
Course Description
Provides a comprehensive study of machine learning algorithms and practical implementations. Covers supervised learning (linear regression, logistic regression, decision trees, random forests, SVM), unsupervised learning (k-means, PCA), model validation metrics, cross-validation, and hyperparameter tuning.
This archive catalogs 7 free educational resources and past exams for IN 404 (Machine Learning) at Purdue University Global (Purdue Global), containing 5 midterm papers, 1 final examination, and 1 quiz. Dated documents represent 6 distinct academic years between 2012 and 2020.
Core Exam Topics & Learning Objectives
- Supervised regression models: ordinary least squares (OLS), Ridge, Lasso, and polynomial regression in IN 404
- Supervised classification algorithms: logistic regression, support vector machines (SVM), and Random Forests for Machine Learning
- Model evaluation and validation: ROC-AUC curves, confusion matrices, precision, recall, and k-fold cross-validation in IN 404
- Unsupervised learning and dimensionality reduction: Principal Component Analysis (PCA) and t-SNE at Purdue Global
Frequently Asked Questions
Which assessment formats are cataloged in this IN 404 archive?
This collection for IN 404 at Purdue University Global (Purdue Global) catalogs 7 total resources across the following formats: Midterms, Finals, Quizzes. Each document is listed in the assessment inventory table with its individual format tag and academic year where recorded.
What academic years are covered in this IN 404 collection?
Dated materials in this archive span from 2012 to 2020, representing 6 distinct academic years. Coverage varies by the records currently cataloged for this course.
How can students access these free IN 404 past exams?
All cataloged IN 404 past exams and study materials are free to request. The catalog, metadata, assessment inventory, and illustrative thumbnails are public; source documents are not shown on this page. Use the connect options to request a study resource, and confirm current course topics and grading policies with the Purdue University Global (Purdue Global) course syllabus.