2018 Maymester Course SA 10503 (ECE 30010) Introduction to Machine Learning & Pattern Recognition This course is designed for Engineering, MGMT, Finance, Science/Technology, Agriculture students and other students from related areas. Students may use this 3-credit course to count toward their plan of study. Course Credits: 3 CREDITS No out of state tuition What’s Included: Acommodation, 3 course credits, cultural events, visit University , expedition and exploration. Irish Tap Dance The Cliffs of Moher Eligibility: All finishing sophomores through graduates Activities: Morning lectures by Purdue Faculty member Afternoon and weekend visitations of historic and cultural sites and museums. Application Deadline: March 1, 2018 Ha'penny Bridge

School of Electrical and Computer Engineering ECE 30010 (SA 10503) PURDUE UNIVERSITY School of Electrical and Computer Engineering ECE 30010 (SA 10503) INTRODUCTION TO MACHINE LEARNING AND PATTERN RECOGNITION Maymester 2019 May 9 – June 1, 2019

Course Objective: To provide the student with the basic topics in machine learning and pattern recognition algorithms such as neural networks, support vector machines, decision trees, data mining and related methods for the design of intelligent and adaptive systems, to describe how they are used in applications, especially involving information and advanced technologies, and to provide hands-on experience with software tools.

Course Description: Intelligent information processing, search and retrieval, classification, recognition, prediction and optimization with machine learning and pattern recognition algorithms such as neural networks, support vector machines, decision trees and data mining methods, current models and architectures, implementational topics, applications in areas such as information processing, search and retrieval of internet data, signal/image processing, pattern recognition and classification, data encryption/decryption, prediction, optimization, simulation, system identification, communications and control.

Classification and recognition are very significant in a lot of domains such as multimedia, radar, sonar, optical character recognition, speech recognition, vision, remote sensing, agriculture, bioinformatics and medicine. We will discuss how intelligent learning algorithms are used in these areas with a number of practical examples from real-world problems.

Prediction is an application domain of classical significance Prediction is an application domain of classical significance. For example, predicting market prices in the near future is an interesting example. What types of signals are predictable? How do linear versus nonlinear prediction techniques compare? What are the best techniques for prediction? We will discuss answers to such significant and practical questions, with illustrations on a number of real-world problems.

System identification is very important, for example, in order to optimize a company’s performance in a defined manner, such as optimization of productivity. For this purpose, it is necessary to do system modeling first. Then, the inputs can be optimized to generate the best output(s) possible from the system. This topic is closely related with system optimization, and techniques such as Six Sigma and Design of Experiments.

Data mining is streamlining the transformation of masses of information into meaningful knowledge. It is a process that helps identify new opportunities by finding fundamental truths in apparently random data. The patterns revealed can shed light on application problems and assist in more useful, proactive decision making. Design of rule-based systems using intelligent learning algorithms is an important topic of this course.

Internet has become a major global mechanism for processing, search and retrieval of information and data, and led to new technologies such as e-commerce, e-business, web-based communications and networking. The algorithms learned in this course are fast becoming major tools for intelligent internet information processing and technology.

As other examples of significant application areas of recent interest, bioinformatics and remote sensing can be cited. Statistical and computational techniques to be discussed in this course have become very important in these and similar areas. In bioinformatics, the application may be DNA sequence analysis, drug design, and similar topics such as proteomics. In remote sensing, the application may be classification and modeling with multispectral, hyperspectral, radar, lidar and optical data.

The algorithms learned in this course are also very important to model and analyze global environmental applications, which are assuming more and more significance.

Prerequisites: Calculus and introductory linear algebra ( probability and statistical concepts used will be introduced during lectures). Homeworks: including MATLAB and Python exercises.

Grade: 35% each exam, 30% homeworks and computer projects Examinations: Two hour examinations. Each hour exam will cover the material between the previous exam and the current exam. Final Project: The final project is a computer project using MATLAB or Python or R. It will be in the form of miniprojects within the homeworks assigned. Grade: 35% each exam, 30% homeworks and computer projects

Textbook: Lecturer’s Course Notes, and Stephen Marshall, Machine Learning, An Algorithmic Perspective, 2nd Edition, Chapman&Hall/CRC Press, 2009, ISBN: 978-1-4665-8328-3 Computer Requirements: ECN dial-up or a PC or Macintosh computer with 256 MB or more of RAM, and 400MB of disk space. Each homework will include Python or Matlab exercises. Matlab 7.0 and above, and relevant toolboxes exist on ECN. Python is open source. Web Learning: The course materials including course notes, homeworks and solutions will be provided by email, web page or other means.

Lecturer: Professor Okan K. Ersoy Office: MSEE 346, Purdue University Phone: (765) 494-6162 Fax: : (765) 494-3358 E-mail address: ersoy@purdue.edu

17

Dublin, Ireland  Dublin is the capital of Ireland and the country’s largest city. It is located on the east coast of Ireland, overlooking Dublin Bay and the Irish Sea. Liffey is the main river running through the city, dissecting it into ‘northside’ and ‘southside’. Dublin is considered the economic and business centre of the country, and the government is here. The city population is 1.3million inhabitants (pop.of Ireland (republic) is c. 4.6millions). In addition to retaining historic and cultural charms, the city mixes contemporary and traditional culture almost at every corner. Here you find the best of elegant cosmopolitan hotels, trendy bars & restaurants as well as great museums and heritage trails.

ST. PATRICK'S AND CHRIST CHURCH CATHEDRALS Ancient, dramatic and intriguing, Dublin’s two cathedrals make a striking pair. Built beside a well where Ireland’s patron saint baptised converts, St. Patrick’s dates back to 1220 and is filled with monuments, 19th century stained glass and a beautiful Lady Chapel. 

THE BOOK OF KELLS AND TRINITY COLLEGE With a historic story that includes monks, Vikings and remote Scottish islands, the Book of Kells is simply sparkling. This glorious Early Christian and illuminated location is quite simply a masterpiece. Located within Trinity College’s Treasury, it includes a visit to the Long Room library, one of Europe’s most magnificent libraries housing over 200,000 of Trinity’s oldest books. 

EPIC The Irish Emigration Museum Located in the historic vaults of the CHQ Building at Custom House Quay, EPIC The Irish Emigration Museum delves into the past of Ireland's diaspora in brilliant interactive detail. The state-of-the-art visitor experience explores the inspiring journeys of over 10 million people who left Ireland's shores throughout history. Fancy learning more about your Irish ancestry? The Irish Family History Centre is also located here, where you can access valuable records, speak with a genealogy expert and join the online community of people on a quest to learn about their Irish roots.

DUBLIN CASTLE Perched on the site of a Danish Viking fortress from 930 AD, and with its first stone cast by King John of England in 1230, Dublin Castle’s historical significance did not stop there. Under British rule from that point until 1921 (it was a key target during the 1916 Easter Rising), it has been a court, a fortress, and even a site of execution in the past,, and its architecture has evolved and grown with each metamorphasis

KILMAINHAM GAOL By the time it had closed in 1924, many of Ireland’s foremost political figures had passed through its cells, including Robert Emmet, Charles Stewart Parnell, President Eamon de Valera, and the leaders of the 1916 Rising (14 of whom were executed in the stonecutter’s yard). The tour here gives a dramatic insight into the history of this notorious prison, with its overcrowding, hardship and brutal conditions. A definite don’t miss.