Sharon Lin
Jan/19 | Fri | 05:00PM-06:00PM | 3-133 |
Enrollment: Unlimited: Advance sign-up required
Prereq: Introductory knowledge of Python recommended
This class will go over the the foundations of understanding Python bytecode and disassembling functions. For anyone interested in understanding how the CPython interpreter compiles source and executes instructions, this is your opportunity to learn more about the Python dataflow and compiler optimizations!
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Sharon Lin, sharonl@mit.edu
Max Shen
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
Our class will explore the intersection between causal inference and deep learning by walking through several recent papers. We aim to highlight several successful ways that deep learning has been used to make headway into important causal questions.
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Max Shen, maxwshen@mit.edu
Max Shen
Julian Hernandez
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
Learn the basics of the artistic and computer sciency side of game design! We'll learn about what makes games fun, how to make decent collision code, the best tools for your sound effects, and how to work in a game dev team without going insane. By the end, you'll have made your own game and be ready to get out there and bring your dreams to life! We'll use GameMaker Studio 2 in the class: it's simple enough that anyone without programming experience can get the hang of it, and it's versatile enough that it's the IDE used for Undertale, Hotline Miami, Spelunky, Hyper Light Drifter, and more!
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Julian Hernandez, gmfk07@mit.edu
Jan/16 | Tue | 05:00PM-07:00PM | 3-333, Bring your laptop. | |
Jan/17 | Wed | 05:00PM-07:00PM | 3-333, Bring your laptop. | |
Jan/18 | Thu | 05:00PM-07:00PM | 3-333, Bring your laptop. |
Julian Hernandez
Lucy Lubashev
Jan/17 | Wed | 06:00PM-07:30PM | 1-135, Bring your laptop. |
Enrollment: Unlimited: No advance sign-up
Have you seen mentions of patents and inventions and tried to read a patent, only to find it unreadable gobbledygook? Are you an inventor and want to know how to proofread a patent application on your invention? Do you need to look through patents for technology valuation? Are you just curious about patent and other IP-related questions and current events? Then come to this class, and you'll learn how to read patents, depending on what your reason for reading them is (No, don't start with the Abstract!), and you'll have a chance to ask your questions to a patent attorney with more than 15 years of experience. Note: this class will not involve reviewing inventions to analyze whether they are ready for patenting.
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Lucy Lubashev, lyudmila@mit.edu
Tristan Naumann
Jan/24 | Wed | 05:00PM-07:00PM | TBD, Bring your laptop. |
Enrollment: Unlimited: No advance sign-up
Prereq: Basic shell familiarity is helpful
Version control systems are essential for the organization of multi-developer projects. Likewise, familiarity with such tools can greatly simplify even small projects. This short course will discuss version control as a problem and focus on how it can be managed with Git. Further, we will discuss how to share code using GitHub and some common workflows.
Git is a free and open source distributed version control system designed to handle everything from small to very large projects. GitHub is a web-based hosting service for projects using Git which has quickly become one of the most popular code repository sites for open source projects.
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Tristan Naumann, tjn@mit.edu
Austin Garrett
Jan/16 | Tue | 05:00PM-07:00PM | 1-115, Bring your laptop. |
Enrollment: Unlimited: No advance sign-up
Prereq: Familiarity with programming is helpful
Pure functions, immutable data, and recursion oh my! Maybe you've heard people talk about functional programming, but what does it all mean?
This class aims to give a general overview of what functional programming is all about, through an introduction to Haskell. Haskell is a pure, strongly-typed functional programming language that has enjoyed a large amount of interest in the past few years. In this talk, I'll try to show you how fun functional programming in Haskell can be, and ultimately how functional languages can help to make your code safer from bugs, more understandable, and simpler (yes, simpler!)
Sponsor(s): Student Information Processing Board, Electrical Engineering and Computer Science
Contact: Austin Garrett, agarret7@mit.edu
James Koppel, Rahul Sridhar
Jan/18 | Thu | 05:00PM-07:00PM | 1-115, Bring your laptop. |
Enrollment: Unlimited: No advance sign-up
Prereq: Familiarity with C and assembly would be very helpful
Is something on your computer hiding something from you? Is it refusing to run unless you do something? Do you want to know exactly what someone else's software is doing? Or perhaps you even want to "open" up some closed-source software and make it do something else. This course will cover the basics of reverse-engineering binaries, as well as some of the ideas of binary modification.
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: James Koppel, jkoppel@mit.edu
Anish Athalye, Logan Engstrom, Andrew Ilyas
Jan/18 | Thu | 05:00PM-09:00PM | 4-237, Bring laptop (Python, NumPy, TensorFlow & Jupyter) |
Enrollment: Unlimited: Advance sign-up required
Sign-up by 01/19
Prereq: MV calc required; linear algebra, Python, NumPy, TensorFlow
Learn the key ideas that make deep learning work.
This class focuses on teaching the mathematical ideas that make deep learning tractable and teaching how to think about deep representations and neural network function approximation.
As we introduce the mathematics, we'll work through implementing simple neural networks and training algorithms from scratch in NumPy. While teaching higher-level ideas, we'll switch to using TensorFlow's high-level interface for programming more sophisticated neural networks without having to think about computing derivatives manually. Finally, we'll introduce cutting-edge ideas from deep learning research, and try to replicate some of the latest results ourselves.
More details here: http://anish.io/deeplearning
Please sign up here: https://goo.gl/forms/lTl5ejUtAY4RJKZQ2
Sponsor(s): Electrical Engineering and Computer Science, Student Information Processing Board
Contact: Anish Athalye, aathalye@mit.edu
Contact Information
COPYRIGHT 2018