ClassInfo

CSC 478 Programming Machine Learning Applications

Winter 2017-2018
Class number: 26163
Section number: 810
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Online Campus

Summary

The course will focus on the implementations of various data mining and machine learning techniques using a high-level programming language. Students will have hands on experience developing both supervised and unsupervised machine learning algorithms and will learn how to employ these techniques in the context of popular applications including automatic personalization, recommender systems, searching and ranking, text mining, group and community discovery, and social media analytics.



Texts

Required: https://www.amazon.com/Machine-Learning-Action-Peter-Harrington/dp/1617290181 Recommended: https://www.amazon.com/gp/product/1491962291


Grading

30% scuiz, 30% assignments, 40% final project.


Prerequisites

IS 467 and CSC 401 Excellent Python programming skills (Python 2.7.12)


Introduction - supervised vs unsupervised - review of numpy and pandas

Data preparation for knowledge discovery - Review of file formats and pandas. Feature extraction. Regression - Logistic Regression - Data Classification. Classification and Prediction using K-Nearest-Neighbor. Decision Trees. Support Vector Machines. Clustering using K-Means and hierarchical algorithms. Classifying text using text frequency analysis (tfidf, Latent Semantic Analysis, Latent Dirichlet allocation) Neural Networks - Overview of Tensorflow and Keras. Optional topics

School policies:

Changes to Syllabus

This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.

Online Course Evaluations

Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation. Students complete the evaluation online in CampusConnect.

Academic Integrity and Plagiarism

This course will be subject to the university's academic integrity policy. More information can be found at http://academicintegrity.depaul.edu/ If you have any questions be sure to consult with your professor.

All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.

Academic Policies

All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at http://www.cdm.depaul.edu/Current%20Students/Pages/PoliciesandProcedures.aspx.

Students with Disabilities

Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296