Xingbei Liu

• A dynamic restaurant website built with the Python Django framework.
• Front-end: Users can browse the menu, reserve tables, and submit contact or feedback forms.
• Back-end: Manage website content, menu items, seat reservations, customer data, and other related information in the database.

• Back-end: Data Filtering and Crawling, Data Management.
• Front-end: Display the first few artifacts from the database in a waterfall layout on the homepage.
• Sorting, Filtering, Fuzzy Search Functionality, and Related Data Management.

• Train a CNN model to recognize cats and dogs, identify dog breeds, and perform multidimensional processing and analysis of the test results.

Implementing machine learning methods from scratch, including:

• Classifiers: decision trees and random forests.
• Clustering: K-means and clustering algorithms.
  Optimization: Gradient descent.
• Algorithm Design: 4-Queens problem and graph coloring using custom algorithms.