• meetup: Merging Differential Equations and Deep Learning

    The Flatiron Institute

    $5.00

    Dr. Christopher Rackauckas, primary author of the JuliaDiffEq packages, Applied Mathematics Instructor at MIT, and Senior Research Scientist at University of Maryland, Baltimore, School of Pharmacy will present an introduction to how Julia's differentiable programming frameworks are bringing neural networks into differential equations and vice versa. Seating is limited. Please arrive 6:00-6:15.

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  • Introducing ITensors.jl

    33 Irving Pl

    $5.00

    Matthew Fishman of the Center for Computational Quantum Physics at The Flatiron Institute introduces us to ITensor.jl, a memory-independent interface for tensor manipulations in Julia. Tensor network methods are an extremely useful class of simulation algorithms in physics. They work by constructing a graph of tensors and making local optimizations to capture the essential physics of a many-body system. ITensor (Intelligent Tensor) is a leading C++ package for work with tensor network methods. In this talk, we present the initial version of ITensors.jl, a ground-up rewrite of ITensor in Julia. Using lessons from the ITensor C++ project, we offer much of the same powerful functionality in a more concise and elegant format, with the goal to substantially lower the "barrier to entry" for using tensor network techniques. We will present some usage examples that are common in physics applications to exemplify the ITensors.jl user interface and design philosophy. Using Julia, we can create a tensor network package expressive enough to capture a variety of physics that's also more easily accessible to working physicists and computer scientists.

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  • Favorite features and demos - Stefan Karpinski (Julia co-creator)

    Please arrive between 6:00 and 6:20.

  • Why I use Julia for Quantum Physics

    The Flatiron Institute

    $5.00

    Katharine Hyatt, PhD from the Center for Computational Quantum Physics at the Flatiron Institute will talk about her own experience using Julia and how it has helped her work in computational quantum physics. Dr. Hyatt has been awarded the Julia Community Prize for all she has done to improve both the test coverage and the documentation of Julia itself.

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  • Tabular Data Frameworks in Julia

    eBay

    $5.00

    We're back and talking data this month with David Gold (https://github.com/davidagold) and Structured Queries (https://github.com/davidagold/StructuredQueries.jl/). Thank you to eBay NYC (http://www.ebaynyc.com/) for hosting. About the talk: This talk will discuss current trends in the development of generic (https://travis-ci.org/JuliaStats/DataArrays.jl) tabular (https://github.com/JuliaStats/NullableArrays.jl) data (https://github.com/davidanthoff/Query.jl) frameworks (https://github.com/JuliaStats/DataFramesMeta.jl) in Julia. We’ll see how Julia’s metaprogramming facilities support a data manipulation/query interface that is generic over different types backends — from in-memory Julia objects to database connections. We’ll also see how the development of such an interface dovetails with work to decouple other related functionality, such as modeling and IO, from Julia's primary tabular data structure, the `DataFrame` type. Finally, we’ll muse on what these current trends might suggest for future development of Julia’s statistics and data science ecosystem. About David: David is a second-year Ph.D. student in the Department of Statistics at the University of Washington (https://www.stat.washington.edu/). He’s been programming in Julia since the spring of 2015. #recursecenter (https://twitter.com/hashtag/recursecenter) We will eat pizza starting at 6:30, talks will start at 7, then we will head to a local bar for drinks and chatting.

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  • Plotting in Julia

    NYU center for data science

    $5.00

    After a break for a few months, the NYC Julia Users meetup group is back! This next meetup will be focused on plotting in Julia. We will have three speakers, each of which will discuss a different package: - Stefan Karpinski: Gadfly.jl (https://github.com/dcjones/Gadfly.jl). Stefan is a co-creator of Julia, a co-founder of Julia Computing, and an employee at the NYU Center for Data Science - Chase Coleman: PyPlot.jl. Chase is a 3rd year PhD student in economics at NYU Stern. - Spencer Lyon: PlotlyJS.jl (https://github.com/spencerlyon2/PlotlyJS.jl). Spencer is a 3rd year PhD student in economics at NYU Stern and the primary author of PlotlyJS.jl. We will eat pizza starting at 6:30, talks will start at 7 and end by 8:30, then we will head to a local bar for drinks and discussion.

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  • Visualization and Learning in Julia

    Kaufman Management Center Room 3-50

    $5.00

    This month we will have Tom Breloff talking about visualization and machine learning in Julia. Pizza from 6:30-7:00. Tom starts at 7:00. By 8:30 we will head to a local bar for a drink. About the talk: We will discuss the plotting ecosystem in Julia, and a new plotting interface and toolset, Plots.jl. We will walk through sample data analysis workflows using Julia packages, and interactively visualize machine learning algorithms using Plots. Bio: Tom worked on Wall St for 10 years as a quant and trader, building high speed trading systems and models, and managing algorithmic trading portfolios. He is currently consulting and working on Julia development full time. https://github.com/tbreloff https://www.linkedin.com/pub/thomas-breloff/b9/910/99

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  • Hands on Intro to Julia

    Kaufman Managment Center Room 5-140

    $5.00

    About the talk: If you've been thinking about trying out Julia but haven't quite gotten around to it, this is your chance. Stefan will give a gentle introduction to the language, show off some of its more interesting features, and take requests for live coding. See how you can write simple Matlab-like code or use multiple dispatch to easily do different things for different kinds of function arguments. Learn how to define your own types and make them work seamlessly with built-ins with minimal hassle. Follow along with your own installation of Julia or use juliabox.org if you don't feel like fussing around with installing all that software. About Stefan Karpinski: Stefan is one of the co-creators of Julia, a research engineer at the NYU Center for Data Science, and a co-founder of Julia Computing, Inc. (juliacomputing.com), providing support, training and consulting for Julia. Pizza will begin at 6:30, the talk starts at 7 and then we will head to a local bar.

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  • The base Julia language: future directions and speculations

    Kaufman Management Center Room 1-70

    $5.00

    Back to the core of Julia this month as we feature Jeff Bezanson. About the talk: Jeff will talk about recent and upcoming developments in the Julia language – its type system, higher-order programming, static analysis and more. If you were at JuliaCon and caught his keynote, some of this will be repeated, but there have been some developments since then too. If you missed JuliaCon, this is a great chance to see Jeff's talk in person. About Jeff: Jeff is one of the co-creators of Julia, as well as a co-founder of Julia Computing, Inc. (juliacomputing.com (http://juliacomputing.com/)), providing support, training and consulting for Julia and its ecosystem. He recently finished his PhD at MIT on the theory and implementation of Julia's type system. Pizza starts at 6:30, Jeff goes on at 7 and then we'll head to a local bar after.

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  • The many ways of parallel computing in Julia

    Kaufman Managment Center Room 5-140

    $5.00

    Short notice but we managed to schedule a meetup for next week featuring Viral Shah. About the talk: This talk will provide an overview of parallel computing in Julia. It will start with an introduction to using built-in Julia primitives for parallel processing (http://julia.readthedocs.org/en/latest/manual/parallel-computing/), such as pmap, @parallel, remotecall, spawn, fetch, etc. Based on this low-level primitives, shared arrays and distributed arrays (https://github.com/JuliaParallel/DistributedArrays.jl) have been built. We will try some Parallel Linear Algebra using packages such as ScaLapack (https://github.com/JuliaParallel/ScaLAPACK.jl) along with some MPI (https://github.com/JuliaParallel/MPI.jl) programming. We will also look at the possibilities of data processing with data loaded from the Hadoop (https://github.com/JuliaParallel/Elly.jl) file system ( (https://github.com/JuliaParallel/Elly.jl)HDFS (https://github.com/JuliaParallel/Elly.jl)) (https://github.com/JuliaParallel/Elly.jl) and/or S3 (https://github.com/amitmurthy/AWS.jl). We will also preview the upcoming multi-threading capabilities in Julia. This work includes contributions by Andreas Noack Jensen, Amit Murthy, Tanmay Mohapatra, Lucas Wilcox, Jiahao Chen, Jake Bolewski, Jeff Bezanson, Keno Fischer, Stefan Karpinski, Kiran Pamnany, Ranjan Ananthraman, Alan Edelman, and many others. About Viral: Viral is one of the co-creators of Julia. Please see the LinkedIn page for more details: https://in.linkedin.com/in/viralbshah We'll start with pizza at 6:30, Viral goes on at 7 then we'll head to a local bar after.

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