My Most Popular Posts of 2017
Although I've made many posts on my Data Analytics Workouts site, some generated more interest than others - nothing here was virally popular - and below are a handful of the most popular, sorted in descending order of views:
- Charting Correlation Matrices in R (877)
- Neural Networks (Part 4 of 4) - R Packages and Resources (507)
- Performance Improvements in R: Vectorization & Memoisation (322)
- Naive Bayes on Political Outcome Based on State-level Big Five Assessment (263)
- Decision Trees on Political Outcome Based on State-level Big Five Assessment (262)
- F# is Part of Microsoft's Data Science Workloads (223)
- Logistic Regression on Stock Data using Google and SPY (SPDR S&P 500) (196)
- Using Visual Studio Team Services for Personal Development (194)
- Microsoft Azure Notebooks - Live code - F#, R, and Python (186)
- Efficient R Programming - A Quick Review (178)
- Patents Per Capita and Hofstede's Cultural Dimensions (167)
- Comparing Performance in R Using Microbenchmark (164)
- Long-term Orientation and Individuality: Obesity Relationships (using R)(149)
- Clustering: Hierarchical and K-Means in R on Hofstede Cultural Patterns (129)
- Attractive Confusion Matrices in R Plotted with fourfoldplot (128)
- Calculating Value at Risk (VaR) with Python or R (119)
- Value-at-Risk (VaR) Calculator Class in Python (114)
The following collection, with some overlap with the list of my most popular posts, are social science related, looking at correlations between personality, culture, politics and human welfare. For cultural dimensions, Geert Hofstede's country-level data was used, while big five personality assessments were used for state-level political prediction. Patent numbers came from WIPO, and social welfare numbers came from the OECD.
- Naive Bayes on Political Outcome Based on State-level Big Five Assessment (263)
- Decision Trees on Political Outcome Based on State-level Big Five Assessment (262)
- Patents Per Capita and Hofstede's Cultural Dimensions (167)
- Long-term Orientation and Individuality: Obesity Relationships (using R) (149)
- Clustering: Hierarchical and K-Means in R on Hofstede Cultural Patterns (129)
- Geert Hofstede | Defined Corporate Culture (108)
- Support Vector Machines on Big Five Traits and Politics (66)
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