chrisshaffer
Quantitative Analytics Specialist at Wells Fargo. I have a PhD in mechanical engineering, focused on neuromorphic circuits for machine learning.
Wells FargoSan Francisco, California
Pinned Repositories
covid-symptom-searches
Are Google searches for COVID-19 symptoms useful in predicting increases in COVID-19 patients? Exploratory data analysis and hypothesis testing using Google's COVID-19 Open Data database.
data_science
ds-precourse-axes
A repository to hold the challenges having to do with modifying the axes on a matplotlib object.
ds-precourse-faceting
ds-precourse-histograms
This repository holds the content for the plotting challenges in the histograms lesson.
ds-precourse-scatterplots
group-playlist-recommender
Companies like Spotify create personalized recommendations. How can this be extended to groups of people? This project uses the Echo Nest Taste Profile of user play histories to create recommended playlists for groups of users.
kaggle-house-price-prediction
My submission to the Kaggle housing price prediction competition, placing in the top 1% of submissions. This uses the XGBoost Regressor, which implements gradient boosted decision trees with high speed and performance.
NN-character-recognition
Neural network-based character recognition using MATLAB. The algorithm does not rely on external ML modules, and is rigorously defined from scratch. A report is included which explains the theory, algorithm performance comparisons, and hyperparameter optimization.
wafer-defect-maps
Inspection equipment for the semiconductor industry saves companies millions of dollars. This project uses the MIR-WM811K Corpus» of wafer maps to build a CNN classifier to automate classification of wafer defect patterns.
chrisshaffer's Repositories
chrisshaffer/wafer-defect-maps
Inspection equipment for the semiconductor industry saves companies millions of dollars. This project uses the MIR-WM811K Corpus» of wafer maps to build a CNN classifier to automate classification of wafer defect patterns.
chrisshaffer/NN-character-recognition
Neural network-based character recognition using MATLAB. The algorithm does not rely on external ML modules, and is rigorously defined from scratch. A report is included which explains the theory, algorithm performance comparisons, and hyperparameter optimization.
chrisshaffer/covid-symptom-searches
Are Google searches for COVID-19 symptoms useful in predicting increases in COVID-19 patients? Exploratory data analysis and hypothesis testing using Google's COVID-19 Open Data database.
chrisshaffer/group-playlist-recommender
Companies like Spotify create personalized recommendations. How can this be extended to groups of people? This project uses the Echo Nest Taste Profile of user play histories to create recommended playlists for groups of users.
chrisshaffer/kaggle-house-price-prediction
My submission to the Kaggle housing price prediction competition, placing in the top 1% of submissions. This uses the XGBoost Regressor, which implements gradient boosted decision trees with high speed and performance.
chrisshaffer/data_science
chrisshaffer/ds-precourse-axes
A repository to hold the challenges having to do with modifying the axes on a matplotlib object.
chrisshaffer/ds-precourse-faceting
chrisshaffer/ds-precourse-histograms
This repository holds the content for the plotting challenges in the histograms lesson.
chrisshaffer/ds-precourse-scatterplots
chrisshaffer/dsi-learn-week0-commandline
chrisshaffer/DSI_Notes_Strategy
A strategy for taking and using quick notes in the Galvanize DSI.
chrisshaffer/dsi_precourse
This is for practice using github/git
chrisshaffer/git-primer-checkpoint
chrisshaffer/Kaggle-Titanic
My submission for the Titanic Kaggle competition with accuracy in the top 7% of submissions. Accuracy was improved by data cleaning to deal with missing values, feature engineering, one-hot encoding of categorical features, use of the XGB Classifier, and hyperparameter optimization.
chrisshaffer/Resume
chrisshaffer/sem-image-recognition
Image recognition of scanning electron microscope (SEM) images using CNNs