Speaker: Daeil Kim is currently a data scientist at the Times and is finishing up his Ph.D at Brown University on work related to developing scalable inference algorithms for Bayesian Nonparametric models. His work at the Times spans a variety of problems related to the company’s business interests, […]
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1. Content: We’ll first introduce the critical text processing operations in R that you’ll need to do any natural language modeling, and then we’ll cover two essential building blocks of NLP: parsing and n-gram models. 2. Speaker: Charlie Redmon, Project Manager of SupStat Inc which is a data analytic consulting and training firm. […]
1. Intro: Vivian will cover the following topic using R: • write short scripts to define a Bayesian model • use or write functions to summarize a posterior distribution • use functions to simulate from the posterior distribution • construct graphs to illustrate the posterior inference And she will show a few real world applications […]
1. Intro: Students of the July-August batch of the beginner Data Science with R course will present their original projects utilizing the data manipulation and visualization skills they learned in the course. 2. Speakers: Sam Chen will be using interactive visualizations in R to explore a range of energy usage metrics by state over time. […]
1. Intro: In this meetup, we’ll talk about which Python distribution to choose and what tools or IDE’s (ipython, ipython notebook, spyder) to use when using Python for development or analysis. We’ll also introduce the Python syntax, built-in data types and functions, loading modules, object oriented programming, etc. At the end of this meetup, we’ll […]
1. Intro: In this meetup, instructor will introduce EDA techniques in R, demonstrating useful (and many times necessary) visual and numerical tests to run on your data before building models and drawing conclusions. 2. Speaker: Charlie Redmon, instructor and project manager at SupStat Inc. 3. Relevant Materials: Meetup Slides: Meetup Video: For a more in-depth […]
1. Intro: This third workshop in the series focuses on simulation-based methods in statistical computing and introduces Monte Carlo integration and ordinary Monte Carlo methods in statistics, then introduces Markov chains and Markov Chain Monte Carlo (MCMC) methods. We will also introduce the Rcpp package for integrating C++ with R. We will explore applications of […]
1. Intro: This second workshop in a three workshop series on statistical computing with C++ introduces two core computational topics in statistical computing: numerical integration and nonlinear optimization. We will also cover the .Call interface between C++ and R. We will introduce Gauss quadrature and the BFGS algorithm for optimization. We will explore the numerical […]
Many thanks go to Special thanks go to Amy for giving such a great workshop! ————————————————————————- NYC Data Science Academy is offering six relative R courses: RSVP RStudio’s Master R Developer Workshop, 2 Days RSVP Data Science with R, Beginner Level RSVP Data Science with R, Intermediate Level RSVP 20 Most Popular R Packages Series – Shiny – Web […]
1. Intro: This was a series of final presentations by students of Introduction to Statistical Programming in Python class by John Downs. The students had to present their final work to the audience which consisted of other students and members of NYC Open Data group. Each presentation highlighted the problem that was under consideration, the […]