Data Science 2: Advanced Topics in Data Science
Advanced data science topics including Bayesian statistics, neural networks, text analysis, and deep reinforcement learning. Meet the instructors Pavlos Protopapas, Mark Glickman, and Chris Tanner, experts in data science and statistics.
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.
E N D
Presentation Transcript
Introduction to CS109B a.k.a. STAT121B, AC209B, CSCI E-109B Data Science 2: Advanced Topics in Data Science Pavlos Protopapas, Mark Glickman, and Chris Tanner CS109A, PROTOPAPAS, GLICKMAN, TANNER 1
Lecture Outline From 109A to 109B Who are we? A walk through the syllabus (i.e., the rules of the road!) Second half of today s lecture starts the new course material! CS109A, PROTOPAPAS, GLICKMAN, TANNER 2
CS109A 1. 2. Regression with continuous outcome 3. Regression with a binary outcome 4. Ethics 5. PCA 6. Decision trees and ensemble methods 7. Basics of Neural Nets 8. Experimental Design Basic statistics, visualization CS109A, PROTOPAPAS, GLICKMAN, TANNER 3
CS109B 1. Smoothing, basis functions, generalized additive models 2. Unsupervised learning 3. Crash course in Bayesian statistics 4. Text Analysis 5. Neural Networks: CNNs RNNs Generative models Reinforcement Learning 6. CS109A, PROTOPAPAS, GLICKMAN, TANNER 4
AC209B 1. Transfer Learning including distillation and compression 2. Segmentation Techniques 3. Echo State Networks 4. Variational Inference 5. Cycle GANS and other GANS techniques 6. Deep Reinforcement Learning CS109A, PROTOPAPAS, GLICKMAN, TANNER 5
Who? Pavlos Protopapas Scientific Director of the Institute for Applied Computational Science (IACS) Teaches CS109(a/b), the data science capstone course and AC295 (advanced practical data science). Research in astrostatistics: machine learning, statistical learning, big data for astronomical problems. He has picked some new hobbies besides 109 and eating: Going to BSO (see you there), cross country ski (completed Engadin skimarathon), cheese making and being a TikToker (check me out @pavlosprotopapas) CS109A, PROTOPAPAS, GLICKMAN, TANNER 6
Who? Mark Glickman Senior Lecturer in Statistics Chess master, inventor of Glicko and Glicko-2 rating systems for head-to-head competition Director of the Harvard Sports Analytics Laboratory Fellow of the American Statistical Association (ASA); Co-Chair of the Ad Hoc Advisory Committee on Data Science of the ASA. Board of Directors member of the American Statistical Association CS109A, PROTOPAPAS, GLICKMAN, TANNER Plays in a rock band called Errors in Bars with three other 7
Who? Instructor Chris Tanner Lecturer at IACS, teaching CS109A and AC297R (capstone) now, and CS109B in the Spring. Research interests are within Natural Language Processing and Deep Learning. Hobbies include hiking and camping, designing/sewing hiking bags, and photography. CS109A, PROTOPAPAS, GLICKMAN, TANNER 8
Who? Lab instructors Eleni Kaxiras Eleni is the assist. Director for Data Science and Computation at SEAS. She has been this course s Head TF for the last 3 years and she is now a lab instructor. She is currently a doctoral student. She is interested in the application of deep learning in analyzing biological signals. She owns olive trees in the island of Crete. CS109A, PROTOPAPAS, GLICKMAN, TANNER 9
Who? Head TF Chris Gumb Chris is currently working towards a graduate degree in Data Science from Harvard Extension School with a particular focus on NLP. His other interests and hobbies include: music theory & jazz improvisation; and film history. CS109A, PROTOPAPAS, GLICKMAN, TANNER 10
Who? Teaching Fellows/Lab Instructors Ioana Zelko Rashmi Banthia Brandon Walker Evan MacKay Sol Girouard Javier Machin Alex Spiride Ani Suresh Marios Matthaiakis Cecilia Garrafo Cedric Flamant Javier Zazo Jin Yun Ethan Cowan Rachel Moon Robert Struyven CS109A, PROTOPAPAS, GLICKMAN, TANNER 11
Magical Mystery Tour of the 109B syllabus A picture containing drawing, food Description automatically generated CS109A, PROTOPAPAS, GLICKMAN, TANNER 12
Help CS109A, PROTOPAPAS, GLICKMAN, TANNER 13
Help The process to get help is: 1. Post the question in Ed and hopefully your peers will answer. We monitor the posts and we will respond within 8 hours from the posting time. 2. Go to Office Hours, this is the best way to get help. 3. For private matters send an email to the Helpline: cs109b2020@gmail.com. The Helpline is monitored by all the instructors and TFs. 4. For personal matters send an email to Pavlos, Mark and Chris. Sundays will be slow days, so please be patient! CS109A, PROTOPAPAS, GLICKMAN, TANNER 14
