jamesquinlan Goto Github PK
Name: James Quinlan
Type: User
Company: University of Southern Maine
Bio: Asst. Professor of Computer Science
Location: Maine
Blog: usm.maine.edu
James Quinlan's Projects
ccar-grid
Cartesian Grid Class
comp-4-data-sci
Computational Techniques for Data Science
cos374-numerical
Introduction to Numerical Analysis
data-structs-algos
Data Structures and Algorithms DSC270
discrete-math
COS 280 - Discrete Mathematics at University of Southern Maine
dsc-techstack
Tech topics for data scientists
dsc130-datasci-r
Course repository for an introduction to data science with R.
fpx
Repository for floating-point explorations
high_performance_computing
Notes & Code from my "High Performance Computing with C" Course
hpr-blas
High-Performance Reproducible BLAS using posit arithmetic
intro-database-sql
Introduction to SQL and Database Design
intro-python
Introduction to Programming and Data Science with Python
intro-stats-mat150
Introduction to Statistics
jamesquinlan
Config files for my GitHub profile.
latestdb
Database of questions (w/solutions) that autogenerator LaTeX file(s)
mat220-linear-algebra
Introduction to Linear Algebra
mathbook
MathBook XML
matlab-programming-intro
Course materials for Intro. to Programming (w MATLAB)
matpak
Matrix utilities, generators, and solvers in MATLAB
ml-su22
nagj
LaTeX template for North American GeoGebra Journal
numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
oer-calculus
Open Educational Resource - PreTeXt (Write Once, Read Anywhere) Calculus Textbook
posit.jl
A posit arithmetic emulator.
principles-programming-languages
Principles and Concepts of Programming Languages
shields
Concise, consistent, and legible badges in SVG and raster format
stats-321
Applied Statistics I (MAT321)
suitesparse
The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University.
syllabus-template
A template for course syllabus in LaTeX.
universal
Large collection of number systems providing custom arithmetic and mixed-precision algorithms for AI, Machine Learning, Computer Vision, Signal Processing, CAE, EDA, control, optimization, estimation, and approximation.
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