Journey of Analytics
|Month/Yr||Project Title||Project Tutorial Description||Download Link|
|Jan 2017||Fitbit Data|
Analyzing data from Fitness trackers. (Fitbit).
Heart rate, sleep quality, calories burned, etc. Tutorial Blog post .
Using 5 machine learning algorithms to predict birth weight of
newborn infants using predictors such as gestation, mother's ethnicity, single or twins/multiples, time when prenatal care started, etc.
Comparison of accuracy and sensitivity from all 5 models. Explanation blog .
|Machine learning models|
|Feb 2017||Ames Housing Sale Prices||Kaggle starter script. Predict house SalePrices using 5 different machine learning algorithms - linear regression, classification trees, neural network, randomforest model, generalized linear model (GLM). Tutorial bloglink.||Ames Housing|
|Apr 2017||Parallel Programming||Parallel Programming in R, including sql queries to retrieve data from database tables. Blogpost link.||Code files|
|May 2017||Dashboards with R|
R Dashboard using:
a) storyboard layout, (b) simple layout with ShinyR elements. Blogpost link.
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2016 Project links are on the Main Projects Page.