parkernisbet Goto Github PK

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Name: Parker Nisbet

Type: User

Bio: Aerospace engineer turned software engineer turned data scientist.

Parker Nisbet's Projects

animal-attribute-clustering

A quick comparison of two (K-Means and hierarchical/agglomerative) clustering methods for text-based animal species classification.

billboard-artist-frequency

Frequency analysis of historical Billboard Hot 100 lists based on an artist's supporting vs main artist numbers.

dask-emnist-classification

Dask-parallelized project, contrasting GaussianNB and LightGBM models for EMNIST handwritten character classification.

drug-use-and-health

A brief look at drug use trends in the United States, as they relate to: earliest age of consumption, and impact on mental health.

game-ab-testing

A/B testing impact of progression system changes on player retention / interaction. Non-parametric hypothesis testing and power transformations for non-normally distributed data.

Partial scratch-implementation of coordinate descent, using a specified feature selector method to choose and later update a coordinate's corresponding weight. This behavior mimics the "fit" function of most descent-compatible machine learning algorithms.

mnist-digit-classifier

Gaussian naive Bayes classifier for digits in the MNIST dataset. Similar in nature to my other repo ("newsgroup-naive-bayes"), albeit instead of multinomial document classification, this repo explores gaussian image classification. Covariance smoothing utilized to minimize error rates to the ~4% realm.

mnist-svm-tuning

Optimizing LinearSVC models trained on the MNIST Handwritten Digits dataset, includes ensemble methods and bayesian optimization.

multiclass-perceptron-boundaries

Quick visualization of linear decision boundaries for a scratch-implemented perceptron classifier. Model evaluates loss function with each weight / bias update and will store away best performing parameters for later use.

newsgroups-naive-bayes

Multinomial naive Bayes newsgroup document classification without relying on pre-built sklearn modules. Smoothing and inverse document frequencies utilized to improve model accuracy.

nintendo-game-ratings

EDA and association rule mining for a Metacritic-sourced dataset of Nintendo games, with comprehensive game-specific data like review scores, release date, developers, genres, and ESRB rating.

online-purchase-propensity

In progress. Modeling shopper purchase propensity for a ficticious online retail website.

parkernisbet

Config files for my GitHub profile.

retail-rfm-analysis

Recency, Frequency, and Monetary Value (RFM) analysis and customer segmentation for transactional data. Unsupervised cluster learning to delineate customer types.

tweet-sentiment-nlp

A notebook covering tweet natural language processing, from data munging to predictive model creation and evaluation. Sentiment analysis will be used to classify tweet body text as positive or negative.

vertebral-neighbors-classifier

Comparison of scratch-implemented and sklearn nearest neighbors methods for classification of vertebral patient data. Using multiple distance metrics, models were k-value optimized to reduce error rates.

xbox-game-pass

Xbox Game Pass subscription value quantification and visualization.

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