All R DataChats

R MACHINE LEARNING

Brett Lantz, 7 Aug 2017

Brett Lantz is a data scientist at the University of Michigan and the author of Machine Learning with R. After training as a sociologist, Brett has applied his endless thirst for data to projects that involve understanding and predicting human behavior.

R R PROGRAMMING

Charlotte Wickham & Oliver Keyes, 30 July 2017

Richie chats to Oliver and Charlotte about the importance of web data, how Oliver isn’t a data scientist, how Charlotte uses data on the web for teaching, web APIs and R packages to access them, web scraping for social good, and data in the cloud vs. computing in the cloud.

R MACHINE LEARNING

Nina Zumel & John Mount, 20 June 2017

Richie chats to Nina and John about their favorite types of regression, statistics vs. machine learning, running Win-Vector, interacting with data scientists vs. interacting with managers, business constraints on models, the vtreat R package, bangra dancing, and life in San Francisco.

R NATURAL LANGUAGE PROCESSING

Julia Silge, 9 June 2017

Richie chats to Julia about her amazing outfit, what is sentiment analysis, data science at Stack Overflow, the importance of community in data science, transferring skills from astrophysics and improv comedy to data science, how the course came about, and text mining gender effects.

R STATISTICS

Rob Hyndman, 4 May 2017

Rob J. Hyndman is Professor of Statistics at Monash University, Australia, and Editor-in-Chief of the International Journal of Forecasting. Rob is the author of over 150 research papers and books in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. He is the author of about 20 R packages, including the popular forecast package.

R STATISTICS

Arnaud Amsellem, 28 April 2017

Arnaud has over 20 years of experience as a quantitative trader. He is creator and author of the R Trader blog (www.thertrader.com).

R R PROGRAMMING

Colin Gillespie, 31 March 2017

Richie chats to Colin about his academic work and consultancy, high performance computing in R, the joy of Fortran 77, how the kids these days have it easy, trends in R usage, efficient programming and premature optimization, and the problem with working while connected to the internet.

R DATA VISUALIZATION

Deepayan Sarkar, 29 March 2017

Richie and Deepayan chat about R-Core and R Foundation, how the lattice project came about, how R has changed over the years, CRAN vs. Bioconductor, how he uses R, and interactive graphics in R. Watch this to find out how to become a member of R-Core, and to hear about Deepayan’s secret use of Python!

R STATISTICS

Barry Rowlingson, 28 March 2017

Richie chats to Barry about tropical diseases, how he became a geographer, R tools for spatial statistics, R and QGIS, the trials of converting between different data structures, the spatial stellar cluster, interactive maps, and trends in spatials stats.

R MACHINE LEARNING

Hank Roark, 11 February 2017

Hank Roark answers Nick's questions about his career into data science, job automation, the importance of communicating your results as a data scientist in both directions and much more!

R FINANCE

Clifford Ang, 19 December 2016

Clifford is a Vice President at Compass Lexecon. He specializes in valuation, corporate finance, and damages, and has worked on hundreds of engagements involving companies across a broad spectrum of industries. He is the author of Analyzing Financial Data and Implementing Financial Models Using R. Together with Lore, Clifford goes over his interest in Finance, his course Bond Valuation and Analysis in R, his latest book and more.

R STATISTICS

Ben Baumer, 19 December 2016

Ben is an Assistant Professor in the Statistical & Data Sciences Program at Smith College. He completed his Ph.D. in Mathematics at the Graduate Center of the City University of New York in 2012. He is an Accredited Professional Statistician™ by the American Statistical Association and was previously the Statistical Analyst for the Baseball Operations department of the New York Mets. Follow Ben here: https://twitter.com/BaumerBen Together with Nick, Ben talks about his path to becoming a sabermetrician, his passion for teaching, the importance of subject-matter expertise in data science and more.

R STATISTICS

Mine Çetinkaya-Rundel, 17 December 2016

Mine is the Director of Undergraduate Studies and an Associate Professor of the Practice in the Department of Statistical Science at Duke University. She received my Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University’s Stern School of Business. Her work focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education. Find Mine's website here: http://www2.stat.duke.edu/~mc301/ Together with Nick, Mine talks about her path into becoming a Statistician, teaching R, trends in the broader data science community and much more.

R STATISTICS

Jo Hardin, 13 December 2016

Jo is a Professor of Mathematics at Pomona College with many years of R experience. She has a pure passion for education and has been working on the ASA’s undergraduate curriculum guidelines where she strongly advocated the infusion of data science into the undergraduate statistics curriculum. Together with Nick, Jo talks about R's place in the stats curriculum, the role of technology in education, what advice she would give to people just starting in statistics, bootstrapping, and much more.

R STATISTICS

David Stoffer, 12 December 2016

David Stoffer is a Professor of Statistics at the University of Pittsburgh. He is member of the editorial board of the Journal of Time Series Analysis and Journal of Forecasting. David is the coauthor of the book "Time Series Analysis and Its Applications: With R Examples", which is the basis of his course. Another (free) book he wrote on Time Series Analysis is available here: http://www.stat.pitt.edu/stoffer/tsa4... Together with Lore, David talks about his path to Statistics, his teaching method, his latest book, how he got into R, and much more.

R STATISTICS

David Robinson, 3 December 2016

Dave is a Data Scientist at Stack Overflow and well known for his blog Variance Explained. He talks about his passion for blogging, the importance of building a data science portfolio, why you should learn SQL and much more.

R DATA VISUALIZATION

Ron Pearson, 4 November 2016

Ron holds a Ph.D. in Electrical Engineering and Computer Science from M.I.T. and has written or co-written five books. Furthermore, he is the author and maintainer of the GoodmanKruskal R package, and one of the authors of the datarobot R package. Together with Nick, Ron talks about his passion for exploratory data analysis, inliers (vs outliers), why he is so excited about the evolution of machine learning models and much more.

R STATISTICS

Charlotte Wickham, 1 November 2016

Charlotte is an Assistant Professor in the Department of Statistics at Oregon State University and an avid R programmer with a passion for teaching. She talks us through her first exposure to R, why a tool like GitHub is fantastic, and how to use your cat and a GPS tracker to collect data for your R coding experiments :-)

R R PROGRAMMING

Garrett Grolemund, 26 October 2016

In this episode, Nick interviews Garrett Grolemund. Garrett is a Data Scientist at RStudio and the author of Hands-On Programming with R and R for Data Science from O'Reilly Media. He talks us through how he discovered R, the evolution of R, what data science means to him and much more.

R MACHINE LEARNING

Max Kuhn, 9 September 2016

In this episode of DataChats, Nick talks with Max Kuhn, the creator of the caret package for R. Max is a frequent speaker at many of the main data science conferences and is well known as the creator of the caret package for R, an essential tool in every R user’s machine learning toolbox. In this 30 min conversation, Max talks about how he originally wanted to become a journalist, why he defines himself as a statistician rather than a data scientist, his thoughts on deep learning, strategies for breaking into the field, and much more.

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