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android-ktx

A set of Kotlin extensions for Android app development.

coding-interview-university

A complete computer science study plan to become a software engineer.

college_access_idx-beyeas01

college_access_idx-beyeas01 created by GitHub Classroom

cutler_decision_tree_random_forests

contains Adele Cutler's random tree algorithm and a bagging algorithm for random forests

data_analyst

Learn to use Python, R, SQL, and Tableau to uncover insights, communicate critical findings, and create data-driven solutions.

freecodecamp

The https://freeCodeCamp.org open source codebase and curriculum. Learn to code and help nonprofits.

fullstack-nanodegree-vm

isdc-projects

Jupyter notebooks completed to help mentor students for Udacity's ISDCND program.

machine-learning-for-trading

Instructor: Tucker Balch (Georgia Tech)

machine-learning-for-trading-1

Code for course: https://classroom.udacity.com/courses/ud501 (Completed!)

machine-learning-for-trading-2

Machine learning techniques learned during CS 7646 applied to trading.

market_simulator

a market simulator that accepts trading orders and keeps track of a portfolio's value over time and then assesses the performance of that portfolio.

market_simulator-1

ml-trading

ml4t

ml4t_coursera

CS7646

ml_trading_assess_learners

machine learning trading algorithms: implement and compare decision tree learner, a random tree learner, and a bootstrap aggregating learner

ml_trading_defeat_learners

machine learning algorithms for trading: implement linear regression and decision tree learners and generate data sets that work better for linear regression and those that work better for decision trees

omscs-ml4t

Projects related to my Machine Learning for Trading course

p1-test-a-perceptual-phenomenon

This is a statistical project that is part of the Udacity Data Analyst Nanodegree. Use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Give your readers a good intuition for the data and use statistical inference to draw a conclusion based on the results.

p2-analyzing-the-nyc-subway-dataset

This is the 2nd project for the Udacity Data Analyst - Nanodegree. The ultimate goal of the analysis is to see whether NYC subway ridership is higher on rainy days vs non-rainy days. Python (NumPy, Pandas, ggplot) and Tableau were used for the analysis and visualizations respectively.

p3-data-wrangling-with-mongodb

This is the 3rd project for the Udacity Data Analyst - Nanodegree. I was tasked at choosing any area of the world from https://www.openstreetmap.org and used data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, to clean the OpenStreetMap data. I chose the GVRD, or Greater Vancouver Regional District, which is my home region. Python was used to clean the data and prepare it for inserting into the NoSQL database: MongoDB. Many queries were then run to arrive at interesting findings. Finally, an R Markdown document was created to easily showcase all the queries in the final pdf report.

p4-data-analysis-with-r

This is the 4th project of the Data Analyst Nanodegree offered by Udacity. In this project, I used R and applied exploratory data analysis techniques to explore relationships in one variable to multiple variables and to explore a selected data set for distributions, outliers, and anomalies.

p5-identifying-fraud-from-enron-email

This is the 5th project as part of Udacity's Data Analyst Nanodegree. In this project, you will play detective, and put your machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.

p6-data-visualization-and-d3

This is the sixth project as part of the Udacity Data Analyst Nanodegee. I created a data visualization from a data set which allows the reader to explore trends or patterns. I used d3.js to create the visualization. My work is a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.

p7-design-an-a-b-test

This is the 7th and final project as part of Udacity's Data Analyst Nanodegree. In this project, I made design decisions for an A/B test, including which metrics to measure and how long the test should be run. Analyzed the results of an A/B test that was run by Udacity and recommended whether or not to launch the change.

project_machine_learning

Machine Learning for Enron. Project #5 for Udacity's Data Analyst Nanodegree program.

project_tableau_story

self-driving-car-nd

Udacity's Self-Driving Car Nanodegree project files and notes.

udacity-intro-to-self-driving-cars

My project repo for Into to Self Driving Cars by Udacity. I am blessed to get Lyft Scholarship for this course.