Pinned Repositories
applying-nearest-neighbors-data-science-intro-000
audiopinion
NLP modeling and statistical analysis of music reviews
dsc-2-20-14-effect-size-p-values-and-power-lab-seattle-ds-career-040119
epicurater
Customer sentiment modelling using online restaurant reviews
ghw2019_lumin_human
Predict economic indicators in data-uncertain regions using satellite images
instrumental_variables
multilingual_machines
Applies BLEU machine translation scores to multilingual patent data
music_reviews
this project conducts hypothesis tests and statistical analysis of Pitchfork music reviews
review_text_classifier
text classification using online customer reviews of restaurants
techniche
Patent signals for machine learning technology decisions
glmack's Repositories
glmack/clustering-seattle-ds-040119
glmack/deeplearning-models
A collection of various deep learning architectures, models, and tips
glmack/docs
TensorFlow documentation
glmack/dsc-04-40-02-introduction-to-neural-networks-seattle-ds-career-040119
glmack/dsc-04-40-03-introduction-to-neural-networks-lab-seattle-ds-career-040119
glmack/dsc-04-40-04-deeper-neural-networks-seattle-ds-career-040119
glmack/dsc-04-40-05-deeper-neural-networks-lab-seattle-ds-career-040119
glmack/dsc-04-41-04-introduction-to-keras-seattle-ds-career-040119
glmack/dsc-04-43-03-convolutional-neural-networks-code-along-seattle-ds-career-040119
glmack/dsc-2-15-06-http-request-response-cycle-lab-seattle-ds-career-040119
glmack/dsc-2-17-02-introduction-summary-seattle-ds-career-040119
glmack/dsc-3-25-04-visualizing-time-series-data-lab-seattle-ds-career-040119
glmack/dsc-3-32-05-gridsearchcv-seattle-ds-career-040119
glmack/dsc-3-32-06-gridsearchcv-lab-seattle-ds-career-040119
glmack/dsc-3-32-10-xgboost-seattle-ds-career-040119
glmack/dsc-3-32-11-xgboost-lab-seattle-ds-career-040119
glmack/dsc-3-35-03-k-means-clustering-seattle-ds-career-040119
glmack/dsc-3-35-04-k-means-clustering-lab-seattle-ds-career-040119
glmack/dsc-3-35-06-common-problems-with-clustering-seattle-ds-career-040119
glmack/dsc-4-38-03-parallel-and-distributed-computing-with-mapreduce-seattle-ds-career-040119
glmack/dsc-4-38-08-rdd-transformations-and-actions-lab-seattle-ds-career-040119
glmack/dsc-4-39-03-collaborative-filtering-singular-value-decomposition-seattle-ds-career-040119
glmack/dsc-4-39-04-singular-value-decomposition-numpy-scipy-lab-seattle-ds-career-040119
glmack/dsc-4-40-01-introduction-seattle-ds-career-040119
glmack/dsc-implementing-recommender-systems-seattle-ds-career-040119
glmack/git
Repository to help me explain git issues!
glmack/movierecommendersystem
glmack/tf_2.0_tutorials
setup tutorial and playgrounds for tensorflow 2.0
glmack/time-series-examples
glmack/fb_lift_study_design
This repository contains code used to calculate the test power and required sample size for Facebook lift studies and multi-cell lift studies.