I'm Arjuna, a Gonzaga Alum who recently graduated with a
B.S. in Computer Science.
I've really been enjoying making visually appealing pages with
HTML/CSS/JS and JS frameworks recently :D
I'm looking to apply these skills and deliver well made frontend
products!
My full name is Arjuna Herbst and I'm a big Manchester City & Gonzaga Basketball fan, and I love getting outside. Currently, I'm seeking opportunities in software development, engineering, or related technical fields where I can leverage my knowledge and learn to solve real-world challenges effectively.
This course covered the basics of computer organization and articheture. This course was taught in C and assembly language. Topics covered included: CPU articheture, ALU's, logic gates, registers, calling functions in assembly, and more. Course Github repo below.
This course served as an introduction to the implementation of machine learning algorithms in Python using Google Colab. Topics covered incduded: linear regression, logistic regression, A* search, model fitting, LLM's, and more. Course Github repo below.
CPSC321 was a course that covered the basics of relational dat abase management. Languages used included SQL, Javascript (Node.js), and Python. Topics covered included: ER diagrams, advanced and basic SQL queries, querying a database from a frontend web application (see project link), and more. See YouTube video on this course's final project below
This course covered principles and techniques of computational complexity. Topics could include dynamic programming, B-trees, minimum spanning trees, Floyd and Warshall algorithms, various string matching algorithms, computational geometry, exponential growth of round-off errors, NP-completeness and reducibility.
In this course, I learned the main components of programming languages and the architecutre of intepreters and compilers. We used Java as a base language to implement our own language called "MyPL". This involved building a lexer, parser, type checker, VM, and code generator to compile MyPL code to bytecode. Also covered was OCaml and functional programming.
This course provided a detailed overview of the processes and techniques used in creating data science applications. Topics included data preparation and cleaning, summary statistics, basic data visualization techniques, feature selection, discretization, k nearest neighbors, naive bayes, decision trees, ensemble methods, apriori rule mining, and k-means clustering.
Built a web page with 3D animations and models using Vite.js with Three.js. May not load properly on smaller devices.
Using Jupyter Notebook, I implemented KNN clustering to analyze NBA 2022-23 player data and find trends and patterns within the data.
Using Node.js, Express, React.js and MySQL Database, I created a web application that allows users to post and leave reviews for their favorite ingredients and recipes.
Using React Native and Supabase, I developed a weather app that provides real-time weather updates and forecasts. Map view is available and you can tap anywhere to get the conditions.
Send me an email and I'll get back to you as soon as possible.
Please provide your name and a brief description of what you're looking for.
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