/BayesInference_latentVariables

The Goal of this assignment is to get you familiar with the basics of Bayesian inference in large models with continuous latent variables, and the basics of stochastic variational inference.

Primary LanguageJupyter Notebook

Assignment 2

Due: 11:59pm Wednesday, March 18

This is the repository for assignment 2. It contains the following files:

  • .gitignore - tells git to ignore certain kinds of files. This prevents you from submitting the auxiliary files created when producing LaTeX documents.
  • README.md - the text you are currently reading.
  • A2.tex LaTeX source for the writeup.
  • A2.pdf assignment text compiled from tex. Please replace with your solutions. Feel free to use Weave.jl
  • Project.toml packages for the Julia environment.
  • A2_src.jl Julia code providing useful functions.
  • A2_starter.jl starter code for assignment in Julia.
  • tennis_data.mat dataset containing outcomes of tennis games.

Submitting with Github Classroom

If you are a registered student in the course, you will receive a link to accept this assignment which will git clone this repository through GitHub Classroom.

If you are registered in the course and did not receive a Github Classroom assignment invitation, contact the instructors!

You will submit your solutions for assessment by using the following git commands in commandline, with git integrated into your editor environment like Atom, or with a dedicated Github application:

  • git status - See what files have been changed, which have been staged (added and ready for a commit), or unstaged and will need to be added.
  • git add - Add all the files you want assessed. Including your .pdf writeup and your source code (.jl, .jmd, or .py)
  • git commit - Saves all the changes that were staged (by git add).
  • git push - Sends your changes off your machine.

Everything you want assessed must be committed and pushed before the assignment due date

Please practice using git and pushing your solutions prior to the deadline. If you have any difficulties, ask on the course forum.

Keep your solutions to this assignment private and in accordance with our collaboration and academic integrity policy.