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Data Science, Machine Learning and Artificial Intelligence

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Christopher Peters, MApStat

Featured recent talk

Statistics, Science and Business

• The Arbitrage Opportunity of Hiring Disabled and otherwise Marginalized People
• How to Calculate Lifetime Value
• The Essential Role of Statisticians in Leading Innovation in Artificial Intelligence: A Case for Diverse Expertise in Tech Leadership
• Beyond Hypothesis Tests & P-values: Iterative Refinement in Science and Business

Statistical analysis

• Are Boeing planes more dangerous than Airbus-produced planes?
• What are the chances the Supreme Court sees turnover in the remaining portion of Trump’s first term?
• Are U.S natural gas pipelines more or less safe?
• Modeling churn
• What’s Y Combinator’s conversion rate?
• A Parable on Customer-base Analysis
• US Treasury Yield Curve

Experiments

• Real-time experiments
• What happens if we peek at experiments?
• How to speed up experiments using pre-treatment variables

Statistical models

• Linear model in stan

Binomial distribution

• Bernoulli experiments in stan
• Binomial distribution
• Binomial relative likelihood and its interval

Exponential distribution

• Relationship of the Generalized Pareto distribution and Exponential-Gamma mixture

Negative binomial distribution

• Relationship of the Negative Binomial distribution and Poisson-Gamma mixture
• Binomial-Negative Binomial experiments
• Zero-inflated negative binomial random numbers
• Zero-inflated negative binomial - generalized exponential random numbers

Poisson distribution

• How and why Poisson regression

Weibull distribution

• Simulating right-censored weibull distributed data
• Frequentist and Bayesian estimating of right-censored weibull parameters

Mixture models

• Relationship of two Gamma distributions and the Beta distribution
• Relationship of the Poisson-Gamma mixture to the Multinomial distribution

Bayesian learning

• Using prior information to reduce sample size requirements
• Geometric distribution and Bayesian updating
• A simple Bayesian bandit

Software musings

• Apache Incubator: graduation rate

R musings

• purrr’s pmap function for mapping functions to data
• Stackoverflow tags complementary to [r] and [python]
• R’s library() function
• A place to learn functional programming in R
• The concept of Either for type-safe error handling in R
• Applying the open/closed principle in R

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Resources that I’ve found useful

• Probability models for customer-base analysis [PDF]
• The log-sum-exp trick for numerical stability
• Statistical Intervals: A Guide for Practitioners and Researchers, Meeker, Hahn and Escobar
• Statistical Methods for Reliability Data, Meeker and Escobar
• Statistical Models and Methods for Lifetime Data, Lawless

Infrastructure

• Ansible
• Ten Things I Wish I’d Known Before Using Vagrant

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@statwonk