Instructor:
Arash Vahdat <avahdat@sfu.ca>

TA:
Hassan Shavarani <sshavara@sfu.ca>

Lab Hours:
Location: Harbour Centre, HCC2960
Tuesdays and Thursdays 17:30-20:20

Office Hours:
Location: Harbour Centre, HCC2960
Sundays 10:00-11:00 AM

Introduction:
Today, machine learning plays a key role in big data analytics. Many internet companies use machine learning to generate value from their planet-size data collected from millions of users in daily bases. After studying basic programming technologies in CMPT 732, in this course, we will learn about using machine learning for analyzing large collections of data. Instead of generating descriptive reports, we will focus on predictive approaches. Our goal in this course is to use machine learning for processing images and text, learning models from labeled and unlabeled data, learning recommendation systems, and analyzing large social networks. We will also study learning techniques for real-time streaming data as well as advanced visualization techniques.

Topics:

• Processing unstructured data (image and text)
• Supervised and unsupervised learning
• Scalable optimization methods
• Recommendation systems
• Social network analysis
• Streaming algorithms
• Anomaly detection
• Visualization

Reference Books

• Learning Spark: Lightning-Fast Big Data Analysis, Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, O'Reilly Media; 1 edition , 9781449358624
• Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills, O'Reilly Media; 1 edition, 9781491912768

Timeline:
The course timeline including the assignments and lecture slides can be found here.

Project:
You can find project guidelines here.