Linear Regression and K-means Clustering With numpy

• Wrote these algorithms entirely from scratch
• Learned about n-dimensional space and matrix algebra/calculus
• Implemented gradient descent and differentiation as methods of regression paramater estimation
• Applied k-means to the infamous iris dataset with the intent of predicting the species clusters:

Actual species grouping versus what K-means predicts:

Regression models on test data using each estimation type:

Sorting Algorithm Visualizations

• PROJECT IN PROGRESS!
• Scraped data from 100 books (title/page length) with python’s bs4 and requests libraries
• In the visualizer, each book is represented by a rectangle with length proportional to the corresponding book’s length
• Scrape data
• Get classes set up for indivudal Books
• Build bubble sort algorithm to sort the books
• Add QuickSort
• Once the framework is stable, add other algorithms: insertion sort, merge sort, etc.
• Get project hosted

Sudoku Solver and Game

• PROJECT IN PROGRESS!
• Implementing a backtracking algorithm to solve sudoku puzzles
• Creating a visualization of the backtracking algorithm
• Creating a simple UI so the game is playable
• Build basic HTML/CSS GUI
• Implement sudoku logic to where game is playable by a person
• Add backtracking algorithm to solve/create new boards
• Make backtrcking algorithm watchable

Currency Market Trading Algorithms

• Created sets of algorithmic rules to attempt to extract profit from currency markets
• Created ggplot2 visualizations of results
• Cleaned/transformed currency data