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- 21 - Episode 21: Behind The Scenes of JuliaCon 2022 With Valentin Churavy
Valentin Churavy joins us to talk about the challenges facing organizers of virtual conferences and what he and the JuliaCon 2022 organizers did to meet those challenges and pull off a successful virtual conference.
We also chat about some of our favorite talks from JuliaCon 2022, and dig into Valentin's background in cognitive science and distributed computing.
Support Talk Julia on Ko-Fi
We're excited to announce that we have opened up podcast memberships! Become a member for as little as $5/mo to get early access to episodes, social media shoutouts, and, starting at $10/mo and up, access to a members-only "office hours" call.
Your support helps us continue to bring you interviews and educational Julia content each week. It also helps us grow sustainably and improve the quality of the podcast.
Manning Publications Discount
We've partnered with Manning Publications to bring all of our listeners a special 35% discount code on all of Mannings physical books, ebooks, courses, and more. There's no expiration date and you can use the discount as many times as you like!
Just visit http://mng.bz/pOzw and use the code
podtalkjulia22
at checkout to get 35% off of your order!Special Guest: Valentin Churavy.
Links:
Julia in VS Code - What's NewJuliaup - The Julia installer and version multiplexerJulia REPL Mastery WorkshopValentin Churavy (Website)Valentin Churavy (Twitter)Valentin Churavy (GitHub)Fri, 19 Aug 2022 - 54min - 20 - Episode 20: From BASIC to Julia: Viral Shah's Julia Journey
Viral Shah, one of the co-creators of the Julia language, join hosts David and Randy to talk about how he got into programming, what led him and his fellow co-creators to create Julia, and his thoughts on the present state and future of the language.
Special Guest: Viral Shah.
Links:
The Julia Programming Language WebsiteJulia Computing WebsiteMon, 23 May 2022 - 1h 04min - 19 - Episode 19: Is Julia Better Than JAX For Machine Learning?
David and Randy respond to an article that makes the case for JAX over Julia for machine learning, particularly when applied to solving differential equations.
David also shares a series of workshops hosted by the Julia Gender Inclusive community, as well as a new package by Elias Carvalho for creating truth tables from Julia expressions, and Randy explores a YouTube series and set of Pluto notebooks all about partially observable Markov processes.
Support Talk Julia on Ko-Fi
We're excited to announce that we have opened up podcast memberships! Become a member for as little as $5/mo to get early access to episodes, social media shoutouts, and, starting at $10/mo and up, access to a members-only "office hours" call.
Your support helps us continue to bring you interviews and educational Julia content each week. It also helps us grow sustainably and improve the quality of the podcast.
Manning Publications Discount
We've partnered with Manning Publications to bring all of our listeners a special 35% discount code on all of Mannings physical books, ebooks, courses, and more. There's no expiration date and you can use the discount as many times as you like!
Just visit http://mng.bz/pOzw and use the code
podtalkjulia22
at checkout to get 35% off of your order!Links:
JAX vs Julia (vs PyTorch) by Patrick Kidger — A while ago there was an interesting thread on the Julia Discourse about the “state of machine learning in Julia”. I posted a response discussing the differences between Julia and Python (both JAX and PyTorch), and it seemed to be really well received! Since then this topic seems to keep coming up, so I thought I’d tidy up that post and put it somewhere I could link to easily. Rather than telling all the people who ask for my opinion to go searching through the Julia Discourse until they find that one post… :D To my mind JAX and Julia are unquestionably the current state-of-the-art frameworks for autodifferentiation, scientific computing, and ML computing. So let’s dig into the differences.Doing small network scientific machine learning in Julia 5x faster than PyTorch by Chris Elrod, Niklas Korsbo, Chris Rackauckas — Machine learning is a huge discipline, with applications ranging from natural language processing to solving partial differential equations. It is from this landscape that major frameworks such as PyTorch, TensorFlow, and Flux.jl arise and strive to be packages for "all of machine learning"... However, the ability to easily construct machine learning libraries thus presents an interesting question: can this development feature be used to easily create alternative frameworks which focus its performance on more non-traditional applications or aspects? The answer is yes, you can quickly build machine learning implementations which greatly outperform the frameworks in specialized cases using the Julia programming language, and we demonstrate this with our new package: SimpleChains.jl.SimpleChains.jl (GitHub)Julia Gender Inclusive (Meetup)Julia Gender Inclusive (Twitter)Learn Julia With Us (YouTube Playlist)Decision Making Under Uncertainty using POMDPs.jl (YouTube Playlist)Decision Making Under Uncertainty (GitHub Repo)POMDPs.jl (GitHub Repo)TruthTables.jl (GitHub Repo)Mon, 16 May 2022 - 48min - 18 - Episode 18: Plotting in Julia (Plots.jl, GadFly.jl, and More)
David and Randy explore Julia's plotting ecosystem and discuss plotting in Julia using Plots.jl, GadFly.jl, VegaLite.jl, Makie.jl, and more.
Support Talk Julia on Ko-Fi
We're excited to announce that we have opened up podcast memberships! Become a member for as little as $5/mo to get early access to episodes, social media shoutouts, and, starting at $10/mo and up, access to a members-only "office hours" call.
Your support helps us continue to bring you interviews and educational Julia content each week. It also helps us grow sustainably and improve the quality of the podcast.
Become a member today 👉 Ko-fi.com/talkjuliapodcast
Manning Publications Discount
We've partnered with Manning Publications to bring all of our listeners a special 35% discount code on all of Mannings physical books, ebooks, courses, and more. There's no expiration date and you can use the discount as many times as you like!
Just visit http://mng.bz/pOzw and use the code
podtalkjulia22
at checkout to get 35% off of your order!Links:
Plots.jl DocsPlotThemes.jl DocsNames Colors ReferenceJulia Visualization Libraries: Which Is Best? (by Emmet Boudreau)Gadfly.jl DocsVegaLite.jl DocsMakie.jl DocsAlgebraOfGraphics.jl GitHubJulia Discourse Visualization CategorySat, 30 Apr 2022 - 37min - 17 - Episode 17: Julia for Data Analysis (with Bogumił Kamiński)
Bogumił Kamiński discusses his new book Julia For Data Analysis (Manning) and his work on the DataFrames.jl package.
📖 Get a permanent 35% discount on Julia For Data Analaysis and every other Manning product 👉 http://mng.bz/pOzw (use code podtalkjulia22)
✨ How to win a FREE copy of Julia For Data Analysis ✨
Share this page on Twitter with the hashtag #JuliaForDataAnalysis and @ mention us (@talkjuliapod). Be sure to follow us on Twitter so that we can DM you the discount code if you win! https://twitter.com/talkjuliapod
Special Guest: Bogumił Kamiński.
Links:
Julia For Data Analysis (use code podtalkjulia22 for a 35% discount)Train Your BrainBogumił's BlogDataFrames.jl (Docs)DataFrames.jl (GitHub)Dagger.jl (GitHub)Fri, 22 Apr 2022 - 1h 05min - 16 - Episode 16: Fast Optimization Using JuMP.jl (with Miles Lubin)
JuMP.jl is a an optimization library written entirely in the Julia language. And it's FAST!
JuMP co-creator Miles Lubin join hosts David Amos and Randy Davila to discuss the inspiration behind JuMP, how JuMP become a NumFOCUS sponsored project, the journey to JuMP's version 1.0 release, and the future of the project.
Special Guest: Miles Lubin.
Links:
JuMP WebsiteJuMP Discourse ForumJuMP DocumentationMiles Lubin's WebsiteMiles Lubin's GitHub ProfileFri, 15 Apr 2022 - 45min - 15 - Episode 15: The Julia REPL is AMAZING (with Miguel Raz)
Once you experience the Julia REPL, it's hard to go back to anything else.
Join hosts David Amos and Randy Davila as we explore the Julia REPL with Julia's official REPL stan Miguel Raz. Miguel shares his Julia story, how Julia is being used in undergraduate courses at Mexico's UNAM, reflects on the willingness of the Julia community to collaborate with other language communities, and teaches us some nifty Julia REPL tips and tricks.
Enjoying Talk Julia?
We're excited to announce that we have opened up podcast memberships! Become a member for as little as $5/mo to get early access to episodes, social media shoutouts, and, starting at $10/mo and up, access to a members-only "office hours" call.
Your support helps us continue to bring you interviews and educational Julia content each week. It also helps us grow sustainably and improve the quality of the podcast.
Become a member today 👉 Ko-fi.com/talkjuliapodcast
Special Guest: Miguel Raz.
Fri, 08 Apr 2022 - 47min - 14 - Episode 14: Making New Math With Julia and Christy.jl
Talk Julia co-host Randy Davila talks about his automated conjecturing program Christy.jl and how he uses it to generate new research problems in graph theory and mathematics using artificial intelligence.
Learn how automated conjecturing works, how Randy got into it, and how Christy.jl can be used to generate problems and potential relations in other domains, too.
Fri, 01 Apr 2022 - 43min - 13 - Episode 13: Serving the Julia Community With Logan KilpatrickFri, 25 Mar 2022 - 53min
- 12 - Episode 12: Easy Input and Beautiful Output With Julia
This week on Talk Julia, David and Randy share and explore resources from around the Julia community all about file input and output and beautiful terminal output. You'll learn how to read and write files in Julia, work the the filesystem, and see how packages like FIGlet.jl and Term.jl can take command line applications to the next level.
Links:
What is file I/O in Julia? by Ifihanagbara OlusheyeFIGlet.jl GitHub RepositoryTerm.jl GitHub RepositoryJulia Machine Learning for Beginners Playlist (Julia for Talented Amateurs)Import and combine multiple .csv files using R and Julia by Guy SuttonThe Julia Language Handbook by George RootFri, 18 Mar 2022 - 33min - 11 - Episode 11: Setting Up VS Code for Julia
Visual Studio Code (VS Code) is a popular code editor from Microsoft, and the Julia VS Code extension makes working with Julia in VS Code a real treat. Learn how to install Julia, VS Code, the Julia VS Code extension, and how to use the Julia VS Code extension features to create a robust and fluid Julia development environment.
Links:
Julia Download PageVisual Studio Code websiteJulia VS Code extension websiteJulia VS Code extension docsJuliaMono websiteJuliaMono GitHub repoSat, 12 Mar 2022 - 36min - 10 - Episode 10: Deep Neural Networks in Julia with Flux.jl
David and Randy explore deep neural networks in Julia using Flux.jl by recreating Grant Sanderson's model for predicting handwritten digits in the MNIST data set. We also show how to visualize model results and training performance in TensorBoard using the TensorBoardLogging.jl package.
Links:
Grant Sanderson's (3blue1brown) Neural networks playlist (YouTube)Neural Network and Deep Learning (Free online book)Flux.jl WebsiteTensorBoard websiteTensorBoardLogger.jl (GitHub)TensorBoardLogger.jl (Docs)Sat, 05 Mar 2022 - 36min - 9 - Episode 9: Learning Flux.jl From a Tensorflow Background
Flux.jl is Julia's elegant machine learning library, but its API is a little different than Tensorflow or PyTorch. This week on Talk Julia, David and Randy dive into Flux.jl, explore some of the big differences between Flux and Python's machine learning libraries, and offer up some tips and tricks for learning Flux if you're coming to it from another ecosystem.
Links:
Flux.jl GitHubFlux.jl WebsiteQuick Overview of Flux.jlRandy's Flux notebooksFlux <3 NumFOCUS — We are very excited to announce that FluxML is partnering with NumFOCUS as an affiliated project to further the cause of open and reproducible science and growing the adoption of the FluxML ecosystem... This partnership will help us in growing the community, bringing new contributors into the ecosystem, and help us manage the funds from future grants we raise for a number of upcoming projects.Fri, 25 Feb 2022 - 36min - 8 - Episode 8: Getting Started With Reinforcement Learning in Julia
David and Randy take a look at reinforcement learning in Julia by diving into the ReinforcementLearning.jl package. We talk a little bit about what reinforcement learning is, as well as our thoughts on ReinforcementLearning.jl's design, which taps into Julia's multiple dispatch system.
About The Show
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.
Links:
Why We Use Julia, 10 Years Later — Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. AlphaGo Documentary (YouTube)An Introduction to ReinforcementLearning.jl: Design, Implementations and Thoughts — The goal of ReinforcementLearning.jl is to provide a collection of tools for learning and implementing reinforcement learning algorithms. This means that, unlike many other existing packages focusing on deep reinforcement learning only, we aim to build a rich ecosystem to solve different kinds of tasks in reinforcement learning.ReinforcementLearning.jl DocsJuliaReinforcementLearning GitHub OrganizationJuliaCon 2022 WebsiteFri, 18 Feb 2022 - 28min - 7 - Episode 7: Are These The Best Julia Packages?
This week we asked Julia Twitter what their favorite Julia packages are, and the responses don't disappoint! We picked two packages to investigate this week: Randy dives into DataFrames.jl and David explores the amazing Revise.jl package.
Randy also shares an example of building a single neuron machine learning model from scratch in Julia, and David talks about some animations he made this week using Javis.jl.
Links:
Twitter thread with everyone's favorite packagesDataFrames.jl DocsRevise.jl DocsRandy's Talk Julia GitHubJavis.jl DocsGist for the circle illusion animationGist for the pulsating circles animationFri, 11 Feb 2022 - 32min - 6 - Episode 6: Exploring Graphs.jl and JuMP.jl in Julia
David and Randy explore graph theory with Juli. We learn how to use the Graphs.jl Julia package to create graph data structures, and the JuMP.jl package to calculate NP-hard and NP-complete properties of the graphs.
This week we also share a bunch of amazing things that our listeners are building in Julia. Thanks to everyone that shared your projects with us! Check out the Twitter thread to see what everyone is working on.
Episode links are available in the show notes on our website ➡ https://www.talkjulia.com/6
ABOUT THE SHOW
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.Links:
Twitter thread showcasing listener projectsHeartBeats.jl by Clemens BrunnerGraphs.jl GitHubGraphs.jl DocumentationJuMP.jl GitHubJuMP.jl DocumentationHearing the Shape of a Graph by Rob EllisThe Music of Graphs by Jason DaviesDavid's script for generating scales and chords from graphsDavid's script for generating a graphs chord and an image of the graphGitHub issue explaining how to use NormalizedLaplacian in Graph.jlJulia Command-line Options (Julia Docs)JULIA_PROJECT Environment Variable (Julia Docs)Fri, 04 Feb 2022 - 27min - 5 - Episode 5: Functions, Methods, Structs, and Style Guides
David and Randy share some of their thoughts on functions, methods, and multiple dispatch in Julia from the perspective as new users coming to Julia from Python.
Learn how Julia's type declarations and multiple dispatch system allow you to redefine functions with different behavior depending on the types of their arguments and explore some of the differences between functions in Julia and functions in Python.
Links:
Functions (Julia Manual)LinearAlgebra bitarray.jl (Julia GitHub)Style Guide (Julia Manual)Methods (Julia Manual)The Unreasonable Effectiveness of Multiple Dispatch (Stefan Karpinski)Types (Julia Manual)Fri, 28 Jan 2022 - 25min - 4 - Episode 4: The Julia Language is Music to Our Ears
David and Randy explore Julia packages for reading, writing, and manipulating music and MIDI files, discuss whether or not Julia should be taught as the primary language in a machine learning course, an amazing Julia resource for Pythonistas, and a whole lot more.
ABOUT THE SHOW
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.Subscribe to our YouTube channel to watch video versions of the podcast, and follow us on Twitter for updates on the show and to connect with David and Randy.
Links:
Hey Julia song by PianoHamsterJuliaMusic.jl GitHubJuliaMusic.jl docsHow To Get a Job Programming In Julia by Logan KilpatrickJulia for Pythonistas Google Colab Notebook by Aurélien Geronjuliabloggers.comThe History of Programming DevCon 2016 Talk by Mark RendleWhy, how, and when of ∘ by Bogumił KamińskiFri, 21 Jan 2022 - 1h 04min - 3 - Episode 3: Penguins, Packages, and Polluting Namespaces
This week on Talk Julia, David and Randy discuss the a cuter alternative to the Iris dataset for teaching machine learning: PalmerPenguin.jl. We also dive into some awesome features of Julia's package manager — namely stacked environments — an awesome You Tube channel for learning Julia, and what the difference between
using
andimport
is when importing a package into your project.ABOUT THE SHOW
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.Links:
Julia in the classroomPalmerPenguins.jl GitHub RepositoryThe Most Underrated Feature of the Julia Language, the Package Manager by Logan KilpatrickWorking With Environments (Julia Docs)Environment Stacks (Julia Docs)JULIA_LOAD_PATH Environment Variable (Julia Docs)Julia For Talented Amateurs (YouTube)Using and Import (Julia Docs)Fri, 14 Jan 2022 - 33min - 2 - Episode 2: Jumping Into Julia From Another Programming Language
Are you you thinking about learning the Julia programming language and you're already fluent in another language, such as R, Python, or MATLAB? In this week's episode, we explore tips, ticks, and resources to help you get up to speed with the Julia language as quickly as possible.
ABOUT THE SHOW
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.Links:
10 Things I Love About Julia by Trang LeThe Julia REPL (Julia Docs)Learn Julia For Beginners – The Future Programming Language of Data Science and Machine Learning Explained by Logan KilpatrickJulia Tutorial by Derek BanasNoteworthy Differences From Other Languages (Julia Docs)MATLAB-Python-Julia Cheatsheet by QuantEconPlots.jl Package DocumentationFri, 07 Jan 2022 - 46min - 1 - Episode 1: Welcome to Talk Julia!
Talk Julia is a weekly podcast devoted to the Julia programming language. Join hosts David Amos and Randy Davila as we explore Julia news and resources, learn Julia for ourselves, and share our experience and everything that we've learned.
This is the first episode of Talk Julia. Learn why we're excited about Julia and what we'll be talking about in future episodes. New episodes will be available every Friday here on YouTube as well as your favorite podcast app.
Sat, 01 Jan 2022 - 9min
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