uoftnotes

📚 Notes for some of my courses at University of Toronto

continued at tingfengx/uclanotes...

Notes that have already finished typesetting:

📒 2021 Winter

• CSC317/CSC418. Identification and characterization of the objects manipulated in computer graphics, the operations possible on these objects, efficient algorithms to perform these operations, and interfaces to transform one type of object to another. Display devices, display data structures and procedures, graphical input, object modelling, transformations, illumination models, primary and secondary light effects; graphics packages and systems. Students, individually or in teams, implement graphical algorithms or entire graphics systems.

📙 2020 Fall

• CSC420. Introduction to basic concepts in computer vision. Extraction of image features at multiple scales. Robust estimation of model parameters. Multiview geometry and reconstruction. Image motion estimation and tracking. Object recognition. Deep Learning approaches to vision.

📘 2020 Winter

• STA414/CSC412. Probabilistic foundations of supervised and unsupervised learning methods such as naive Bayes, mixture models, and logistic regression. Gradient-based fitting of composite models including neural nets. Exact inference, stochastic variational inference, and Marko chain Monte Carlo. Variational autoencoders and generative adversarial networks.
• CSC309, Programming on the Web. Notes on technical stuff covered in the course.
• ENV200, Science and Environment. Consisting of notes from the book and lecture slides. (Archived)
• CSC413 (Archived). An introduction to neural networks and deep learning. Backpropagation and automatic differentiation. Architectures: convolutional networks and recurrent neural networks. Methods for improving optimization and generalization. Neural networks for unsupervised and reinforcement learning.

📗 2019 Fall

• CSC258, Computer Organizations. In plain HTML. Topics include computer structures, machine languages, instruction execution, addressing techniques, and digital representation of data. Computer system organization, memory storage devices, and microprogramming. Block diagram circuit realizations of memory, control and arithmetic functions.
  • Midterm Pre-test checklist
  • Final Review Notes (Mainly On Assembly)
• PHL245, Modern Symbolic Logic. (Currently archived)
• CSC311, A cheat sheet for the exams, as allowed by the course syllabus. (Archived) Please note that this version was not finished. If you want to find an usable open source cheat sheet for CSC311, I point you to these aid sheets by @AndyTQ.
• CSC373, Miscellaneous notes from MIT open courseware (6.006 and 6.046J). Focusing on NP-completeness: polynomial time reductions, examples of various NP-complete problems, self-reducibility.
• STA302. Introduction to data analysis with a focus on regression. Initial Examination of data. Correlation. Simple and multiple regression models using least squares. Inference for regression parameters, confidence and prediction intervals. Diagnostics and remedial measures. Interactions and dummy variables. Variable selection. Least squares estimation and inference for non-linear regression.

📕 2019 Winter

• MAT224, Linear Algebra II. Collection of (nearly) all the theorems presented in the book/mentioned during lecture. Topic include fields, complex numbers, vector spaces over a field, linear transformations, matrix of a linear transformation, kernel, range, dimension theorem, isomorphisms, change of basis, eigenvalues, eigenvectors, diagonalizability, real and complex inner products, spectral theorem, adjoint/self-adjoint/normal linear operators, triangular form, nilpotent mappings, Jordan canonical form.
• STA261, Statistics II. A manuel for common test statistics. Topics include statistical models, parameters, and samples. Estimators for parameters, sampling distributions for estimators, and the properties of consistency, bias, and variance. The likelihood function and the maximum likelihood estimator. Hypothesis tests and confidence regions.
• MAT237, Advanced Calculus. A Collection of Theorems, with focus on fall 2018 term which was not present in the notes that I typesetted together with @yuchenWYC. Topics include sequences and series. Uniform convergence. Convergence of integrals. Elements of topology in R^2 and R^3. Differential and integral calculus of vector valued functions of a vector variable, with emphasis on vectors in two and three dimensional euclidean space. Extremal problems, Lagrange multipliers, line and surface integrals, vector analysis, Stokes' theorem, Fourier series, calculus of variations.

Other notes that I participated in typesetting:

• MAT237, Advanced Calculus, a short guide to theorems, lemmas and propositions. This particular set of notes was made together with @yuchenWYC. @AndyTQ et al. also made some useful comments for the improvment of the .tex file. They are available here.

💻 Typesetting in \LaTeX

Most of these notes were written with a software called TeXpad. Unfortunatelly, this brilliant application is only available on MacOS right now. But if you are using a Mac, I would highly recommend you try it out. (I was not paid by TeXpad in anyway lol. )

$ pdflatex --version
pdfTeX 3.14159265-2.6-1.40.20 (TeX Live 2019)
kpathsea version 6.3.1
Copyright 2019 Han The Thanh (pdfTeX) et al.   

$ latexmk -version
Latexmk, John Collins, 26 Dec. 2019. Version 4.67

$latex = 'latex -interaction=nonstopmode -shell-escape';
$pdflatex = 'pdflatex -interaction=nonstopmode -shell-escape';

Template

Check out my commands and templates at https://tingfengx.com/tex/.

License

Unless otherwise stated, all files in this repo are licensed under Attribution-NonCommercial-ShareAlike 4.0 International. You can find the full legal code as well as its translations here. By the license, in human readable words, you are free to

• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material

under the following terms:

• Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
• NonCommercial — You may not use the material for commercial purposes.
• ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
• No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Note:

• You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. I.e., The rights of users under exceptions and limitations, such as fair use and fair dealing, are not affected by the CC Licenses.
• No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

Credits

• The markdown version of the license is from https://github.com/idleberg/Creative-Commons-Markdown by @idleberg
• CC License badges are from https://gist.github.com/lukas-h/40df8fcbac877be380591787e4af996c by @lukas-h
• Open Source badge from https://github.com/ellerbrock/open-source-badges/ by @ellerbrock
• View count badge from https://github.com/dwyl/repo-badges by @dwyl