Example Test Cases for Stanford's Algorithms Coursera Specialization

Collection of solutions that I come up with for the Stanford CS106A course.

Courses from MIT, Harvard, Stanford, Yale, Penn

CS106a: Programming Methodology files--created at Stanford University in Summer 2013.

Custom Emotion Annotator for Stanford CoreNLP Java

Elyryde is a mobile application that allows owners of electric vehicle charging stations to list them and generate revenue from them. Submission for TreeHacks 2021 by Stanford

Natural language processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze large amounts of natural language data.

A simple encryption/decryption system for hex-encoded ciphertexts using the same stream cipher key.

stanford Java NLP English vocabulary analysis and sentence analysis

CS 61B Data Structures, Spring 2021

Keyword Extraction

Clack is a graphic router written in Java to help teach core concepts for a university-level network course.

This game is a simple bricks breaking game.

The Stanford NER (named entity recognition) wrapper with an API setup. Pull in your Stanford NER result into your Javascript app for AI usage.

Happy Programming! Karel the robot learns Java. Remove the complicated technicality of language and keep the pure algorithm

native implementation of the binary search tree

This is a simple sentiment analysis project using Java. With explanation of methods and objects.