I am David Raymond Kearney, political economist by training, data scientist by profession.
As a data scientist, I create automated member and provider engagement campaigns that leverage e-mail, IVR, SMS and live calls to increase medication adherence.
I also design experiments and employ randomized control trials to improve campaigns by identifying the most effective campaign variants, and productionlize machine learning models to identify members at risk of behaving in a way that contributes to poor health outcomes and most likely to benefit from campaigns.
I got my Ph.D. at Duke University, where my research focused on applying econometric and statistical techniques to explain and predict the allocation of fiscal transfers.
This site, will cover spark, h2o. hive and data science using python.
Posts
AutoML, Xgboost and H2O
Adam optimizer
Text Generation - LSTM
Timeseries
Tensorflow and Keras
Pytorch
Using Prophet for S&P 500 forcasting
Dask API for analytics
Using Dask and dask-sql
NLP Example bằng tiếng Việt using StackNetClassifier
Spacy in Python for Natural Language Processing (NLP) Example
Kaggle Submission Example
World Cup prediction example
Webscraping Text and Images with BeautifulSoup example
Setting up pyspark locally, for development.