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Showing posts from December, 2017

Review: Complex Adaptive Systems: An Introduction to Computational Models of Social Life

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Complex Adaptive Systems: An Introduction to Computational Models of Social Life by John H. Miller My rating: 4 of 5 stars A thought-provoking introductory exploration to modeling social systems, covering ideas for rule-based agents within a variety of rule-based systems, moving onto evolutionary-like automata and organization of agents to solve problems. Underlying some of the ideas, one could see references to deeper concepts, e.g., nonlinearity, attractors, emergence, and complexity, none of which was explained explicitly. At times, I did find the writing tedious, as some ideas were too obvious to spend time detailing, but overall, a well-written easy to digest text. View all my reviews

My Most Popular Posts of 2017

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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 Usin