Using Python and Flask, created a working application to abstract backend processes, making it easier to view, add, and alter information on a multi-network database and API.
Using React Native, created a working application for the New Mexico United Team to support fanbase, shop, match updates, and team information.
The use (or lack thereof) of contraceptive methods can be strongly affected by demographic and socio-economic factors. Being able to predict the use from the factors, allows for better marketing or advertising to targeted groups. With this goal, we attempted to be able to predict the use of contraceptives (no use, short term, long term) from looking at certain demographic and socio-economic features. Upon the creation of many models (including LogisticRegression, Cross-Validation, Random Forests, etc) plus analysis to find the most highly correlated features and the addition of hyperparameters, we were able to achieve a training accuracy of 72%.
I created my first ever wesbite! Created completely from scratch, utilising CSS, HTML, JavaScript, and bootstrap. I self taught myself everything that I created on this website, and got to put my own personality into it.
I am working on the website for Maggie Sokolik's College Writing Program, complete with a online course and online shopping module.
I created a mini version control system modeled after git. It supported the following commands: init, add, commit, rm, log, global-log, find, status, checkout, branch, rm-branch, reset, merge, add-remote, push, pull, and delete-remote. I utilized SHA1 serialization for file tracking.
I recreated a board game called "Tablut", based on an ancient Nordic and Celtic strategy board game played on a checkered or latticed gameboard with two armies of uneven numbers. In my iteration, you can either play the game through terminal commands, or through a GUI I built. I also created a complex AI, which was designed to force a win within 4 moves if possible for whichever side it played.
I recreated the Enigma Machine which was used for encryption during WWII. My project takes a .in text file with a message, and encrypts it given a rotor setting, plug board, alphabet, and ring setting (Ringstellung). It outputs to a .out file. The machine can also take in an output, and decrypt the mesage to the given alphabet. The encryption process follows that of the original machine!
I created a Heart Disease Classifier that could predict whether you had heart disease or not given a persons age, Resting BP, cholestoral, Maximum heart rate, Excersize vs Resting heart rate, and Normal vs defect heart rate. My data set came from a kaggle data set that I cleaned. For my classifier, I used a K Nearest Classifier and a cross Validation test, with libraries such as numPy and scikit-learn.
I created a Movie Disease Classifier that could predict the genre of a movie based on the occurance of 20 different words in the script. My data set came from Berkeley's Data 8 class. For my classifier, I used a K Nearest Classifier with multiple trials of arbriatry k-values.
I created a large scale case study into cause and effect surrounding cardiovascular disease. I looked through multiple data sets from multiple decades, provided by Berkeley's Data 8 class, to create a hypothesis test analyzing if poor diet caused heart disease.
I created data visualizations on graduate admission statistics to analyze commons questions about the dataset including: Are GRE and TOEFL scores positively correlated?, Do higher GRE and TOEFL scores increase the chance of getting into a Master’s program?, Does having a higher GPA increase your chance of Admit?, and others. It plays an important role in analyzing what factors affect graduate admissions and what students should focus when applying.
I created revamped the old Berkeley Law website to its current version using HTML and Wordpress.
I created a scheme interpreter which is able to read any scheme input and perform the correct operation, and carry out basic operations. It had a few core functionalities: The evaluator, User defined procedures, and Special Forms.
I created a game called Ants vs SomeBees, which is a turn based game where ants defend their colonies and bees try to attack said colonies. Different type of ants have different characteristics and attack abilities, as do queen bees.
I created a visualization of restaurant ratings using machine learning. It allows users to view resturaunts that match their previous preferences based on location and ratings. It utilises a voronoi diagram.
I created a game called hog which is a turn based game that utilizes die, random chance, and strategy. The goal of the game is to get to 100 total points, where points are the sum of the dice outcomes.
I created a mini version control system modeled after git. It supported the following commands: init, add, commit, rm, log, global-log, find, status, checkout, branch, rm-branch, reset, merge, add-remote, push, pull, and delete-remote. I utilized SHA1 serialization for file tracking.
I recreated a board game called "Tablut", based on an ancient Nordic and Celtic strategy board game played on a checkered or latticed gameboard with two armies of uneven numbers. In my iteration, you can either play the game through terminal commands, or through a GUI I built. I also created a complex AI, which was designed to force a win within 4 moves if possible for whichever side it played.
I recreated the Enigma Machine which was used for encryption during WWII. My project takes a .in text file with a message, and encrypts it given a rotor setting, plug board, alphabet, and ring setting (Ringstellung). It outputs to a .out file. The machine can also take in an output, and decrypt the mesage to the given alphabet. The encryption process follows that of the original machine!
Using Python and Flask, created a working application to abstract backend processes, making it easier to view, add, and alter information on a multi-network database and API.
I created a Heart Disease Classifier that could predict whether you had heart disease or not given a persons age, Resting BP, cholestoral, Maximum heart rate, Excersize vs Resting heart rate, and Normal vs defect heart rate. My data set came from a kaggle data set that I cleaned. For my classifier, I used a K Nearest Classifier and a cross Validation test, with libraries such as numPy and scikit-learn.
I created a Movie Disease Classifier that could predict the genre of a movie based on the occurance of 20 different words in the script. My data set came from Berkeley's Data 8 class. For my classifier, I used a K Nearest Classifier with multiple trials of arbriatry k-values.
I created a large scale case study into cause and effect surrounding cardiovascular disease. I looked through multiple data sets from multiple decades, provided by Berkeley's Data 8 class, to create a hypothesis test analyzing if poor diet caused heart disease.
I created data visualizations on graduate admission statistics to analyze commons questions about the dataset including: Are GRE and TOEFL scores positively correlated?, Do higher GRE and TOEFL scores increase the chance of getting into a Master’s program?, Does having a higher GPA increase your chance of Admit? , and others. It plays an important role in analyzing what factors affect graduate admissions and what students should focus when applying.
I created a scheme interpreter which is able to read any scheme input and perform the correct operation, and carry out basic operations. It had a few core functionalities: The evaluator, User defined procedures, and Special Forms.
I created a game called Ants vs SomeBees, which is a turn based game where ants defend their colonies and bees try to attack said colonies. Different type of ants have different characteristics and attack abilities, as do queen bees.
I created a visualization of restaurant ratings using machine learning. It allows users to view resturaunts that match their previous preferences based on location and ratings. It utilises a voronoi diagram.
I created a game called hog which is a turn based game that utilizes die, random chance, and strategy. The goal of the game is to get to 100 total points, where points are the sum of the dice outcomes.
Using React Native, created a working application for the New Mexico United Team to support fanbase, shop, match updates, and team information.
I created my first ever wesbite! Created completely from scratch, utilising CSS, HTML, JavaScript, and bootstrap. I self taught myself everything that I created on this website, and got to put my own personality into it.
I am working on the website for Maggie Sokolik's College Writing Program, complete with a online course and online shopping module.
I created revamped the old Berkeley Law website to its current version using HTML and Wordpress.
The use (or lack thereof) of contraceptive methods can be strongly affected by demographic and socio-economic factors. Being able to predict the use from the factors, allows for better marketing or advertising to targeted groups. With this goal, we attempted to be able to predict the use of contraceptives (no use, short term, long term) from looking at certain demographic and socio-economic features. Upon the creation of many models (including LogisticRegression, Cross-Validation, Random Forests, etc) plus analysis to find the most highly correlated features and the addition of hyperparameters, we were able to achieve a training accuracy of 72%.
I created a Heart Disease Classifier that could predict whether you had heart disease or not given a persons age, Resting BP, cholestoral, Maximum heart rate, Excersize vs Resting heart rate, and Normal vs defect heart rate. My data set came from a kaggle data set that I cleaned. For my classifier, I used a K Nearest Classifier and a cross Validation test, with libraries such as numPy and scikit-learn.
I created a Movie Disease Classifier that could predict the genre of a movie based on the occurance of 20 different words in the script. My data set came from Berkeley's Data 8 class. For my classifier, I used a K Nearest Classifier with multiple trials of arbriatry k-values.
I created a large scale case study into cause and effect surrounding cardiovascular disease. I looked through multiple data sets from multiple decades, provided by Berkeley's Data 8 class, to create a hypothesis test analyzing if poor diet caused heart disease.
I created data visualizations on graduate admission statistics to analyze commons questions about the dataset including: Are GRE and TOEFL scores positively correlated?, Do higher GRE and TOEFL scores increase the chance of getting into a Master’s program?, Does having a higher GPA increase your chance of Admit?, and others. It plays an important role in analyzing what factors affect graduate admissions and what students should focus when applying.