Julia for Public Health: As the infectious coronavirus causing COVID-19 spreads worldwide, we highlight two Julia developments in the area of public health: Pumas for accelerating clinical trials through a modern software stack, and a new paper on Infectious Disease Transmission Network Modelling with Julia by Justin Angevaare, Zeny Feng and Rob Deardon.
Converting SAS Applications to Julia: Are you interested in converting SAS applications to Julia? Julia Computing partners with Great Lakes Consulting Services to help you accelerate replacement of existing SAS applications, improve performance, reduce development time, augment or replace existing systems and provide an extended trusted team to deliver Julia solutions. Leverage experienced resources from Julia Computing and Great Lakes Consulting Services to get your team up and running quickly. For more information, please contact us at [email protected].
New JuliaTeam Release: JuliaTeam from Julia Computing provides enterprise governance including private and package development, deployment, management, security, support and indemnification. The newest release:
Supports Julia 1.4 and beyond
Supports the latest Julia package protocol
Provides new and simplified authentication systems that create a
more robust user experience
Allows users to run JuliaRun jobs with any major cloud provider -
AWS, Azure or GCP
Upcoming Julia Computing Online Events: Julia Computing provides a number of free and affordable Webinars, micro-trainings and trainings on a wide range of topics. Click the links below to register.
Date and Time
Fri Mar 6 11:30 AM to 12:30 PM London (UK)
Pharmacology and Pharmacometrics with Pumas
Dr. Vijay Ivaturi, Professor of Pharmacology and Pharmacometrics, University of Maryland, Baltimore
Fri Mar 13 12:00 PM to 1:00 PM Eastern (US)
Putting a Trained ML Pipeline Behind a Webserver to Serve It
Dhairya Gandhi, Julia Computing
Fri Mar 20 12:00 PM to 1:00 PM Eastern (US)
Financial Modeling on Large Streaming Datasets
Dr. Josh Day, Julia Computing
Fri Mar 27 12:00 PM to 1:00 PM Eastern (US)
Building and Deploying an NLP Model in Julia
Deepak Suresh, Julia Computing
Wed Apr 15 and Thu Apr 16 11:00 AM to 3:00 PM Eastern (US)
Online Instructor-Led Training
Intro to Julia
Dr. Matt Bauman, Julia Computing
Wed Apr 22 and Thu Apr 23 11:00 AM to 3:00 PM Eastern (US)
Intro to ML and AI in Julia
Wed Apr 29-Thu Apr 30 11:00 AM to 3:00 PM Eastern (US)
Parallel Computing in Julia
Julia Returns to Google Summer of Code: Julia returns to Google Summer of Code in 2020. Proposals may be submitted beginning March 16. More information is available here including application guidelines and project ideas.
Google Code-In Contest: Avik Sengupta, Dhariya Gandhi and Logan Kilpatrick published a blog post about Julia’s first year of participation in Google Code-In: “Over the last couple of months, 212 young people have completed over 690 tasks using Julia as part of the Google Code-In program.” More information is available here.
JuliaCon 2020 Deadlines: JuliaCon 2020 will take place July 27-31 at ISCTE - Instituto Universitário de Lisboa (ISCTE-IUL) in Lisbon, Portugal.
JuliaCon 2020 Call for Proposals: JuliaCon 2020 proposals are due March 7, 2020. Proposal types include talks, lightning talks, minisymposia, workshops, posters and ‘Birds of a Feather’ breakout sessions. Please review submission guidelines, prepare and submit your proposal no later than March 7, 2020. Mentorship is also available for new presenters.
Financial Assistance to Attend JuliaCon 2020: If financial assistance will impact your ability to attend JuliaCon 2020, please apply no later than March 7, 2020.
Early Bird Ticket Discount: Early Bird Tickets are available for purchase now through April 20, 2020. Please purchase your tickets early to take advantage of discounted pricing.
JuliaCon 2020 Call for Volunteers: JuliaCon runs on volunteers! Please consider signing up to volunteer. JuliaCon volunteer opportunities include:
Julia Voted “Most Exciting New Computer Language” for Bioinformatics: Bioinformaticians have voted Julia the “most exciting new computer language” for bioinformatics.
Julia Package GitHub Star History: Julia Computing’s Patrick Mogensen shared this graph of the GitHub star history for several popular Julia packages.
Is Python Finally Catching Up to Julia? Roger Luo notes that a popular Yao.jl technique for multi-QPU quantum computing is now available in Python.
Julia en Français: Une Introduction à Julia is available en Français.
Julia Alternatives to Python Pandas: Viral Shah, co-creator of Julia, co-founder and CEO of Julia Computing provided an answer to the question: What Are Some Alternatives to Python Pandas? Click here to see the answer.
Hands-On Design Patterns and Best Practices with Julia (Packt): Tom Kwong has published Hands-On Design Patterns and Best Practices with Julia. This book is a collection of patterns, documenting the best approaches to designing high-quality Julia applications. Its purpose is to provide developers with guidance on how to design and develop software in Julia and to serve as a reference for future discussions regarding design patterns in Julia. The book’s forward was written by Julia co-creator and Julia Computing co-founder Stefan Karpinski.
New Threading Capabilities in Julia v1.3: Jameson Nash (Julia Computing), Jeff Bezanson (co-creator of Julia and co-founder of Julia Computing) and Kiran Pamnany (Caltech) wrote an article published by Intel titled New Threading Capabilities in Julia v1.3. The article explains how Julia v1.3 facilitates multithreading quickly and easily.
LightGraphs Benchmarking: Tim Lin (Lynx Analytics) has produced new benchmarks comparing LightGraphs.jl with other popular graph packages. Special thanks to Seth Bromberger who suggested adding LightGraphs.jl to this benchmarking exercise.
Julia Helps Shed Light on the Origins of the Universe: Cosmologist Marius Millea uses Julia to develop next-generation tools to analyze the lensed Cosmic Microwave Background. More information is available on GitHub and Twitter.
Julia for Oceanography: Gael Forget (MIT) presented Julia Users and Tools for Oceanography at the Ocean Sciences Meeting in San Diego on February 18.
Coding the Mandelbrot Set in Julia (with GPU): Ole Kröger has released a new YouTube video on Coding the Mandelbrot Set in Julia (with GPU).
Enigma: Ole Kröger has released a new YouTube video titled Enigma: Endless Possibilities Is Not Enough.
Julia for Econometrics: Romeo Greminger published a presentation on Julia for Structural Econometrics (or: How I Learned to Stop Vectorizing and Love Julia).
Natural Language Processing in Julia: Ayush Kaushal, Lyndon White, Mike Innes (Julia Computing) and Rohit Kumar have published a paper in the Journal of Open Source Software titled WordTokenizers.jl: Basic Tools for Tokenizing Natural* *Language in Julia.
Deep Learning Using Neural Networks in Julia: Alex Luedtke, Marco Carone, Noah Simon and Oleg Sofrygin published Learning to Learn from Data: Using Deep Adversarial Learning to Construct Optimal Statistical Procedures in Science Advances. “For a two-dimensional generalized linear model, we found that it took approximately 40 times as long to evaluate our procedure on a dataset as to run a generalized linear model in Julia… We also compared the runtime of our learned clustering procedure to the EM and k-means implementations that we used, both of which were based on Julia code from publicly available repositories—links to these repositories can be found in our source code. On 10,000 randomly generated datasets, our learned procedure, on average, evaluated approximately 10 times faster than k-means and 400 times faster than EM. This improved runtime came at the cost of an initial offline training time of 6 hours on a GPU cloud computing service… We learned and interrogated our procedures in Julia. The neural networks for the point estimation and prediction experiments were fitted using Knet, and the neural networks for the confidence region construction experiments were fitted using Flux.”
New Papers from Timothy Holy Featuring Julia: Timothy Holy, Professor of Neuroscience at Washington University in St. Louis, has co-authored two new papers featuring Julia: Sensory Coding Mechanisms Revealed by Optical Tagging of Physiologically Defined Neuronal Types by Donghoon Lee, Maiko Kume, Timothy Holy and Fast Objective Coupled Planar Illumination Microscopy by Cody Greer and Timothy Holy.
Julia Computing Enterprise Solutions: Contact Julia Computing for more information about putting Julia to work for your organization, deploying Julia more efficiently, effectively and at scale.
JuliaSure: JuliaSure provides enterprise support and indemnification for organizations using Julia.
JuliaTeam: JuliaTeam provides enterprise governance including private and package development, deployment, management, security, support and indemnification.
JuliaRun: JuliaRun allows you to scale Julia deployment from a single machine to dozens or hundreds of nodes in a public or private cloud environment, including AWS, Azure or Google Cloud.
JuliaBox 30 Day Free Trial: JuliaBox is now available with a 30 day free trial. JuliaBox is the fastest and easiest way to start using Julia right away with no download required. Register today to start your 30 day free trial.
JuliaBox Academic Discount: Hundreds of students and faculty at universities around the world use JuliaBox for classroom instruction and learning. Use free and open source materials to design your own course using Julia. JuliaBox starts at just $7 per month including a 50% academic discount. Sign up online or contact Julia Computing to take advantage of the academic discount or for more information.
Julia and Julia Computing in the News
Analytics India: Top 6 Must-Attend AI & ML Conferences in India for 2020
IProgrammer: Hands-On Design Patterns and Best Practices with Julia (Packt)
MIT News: Brainstorming Energy-Saving Hacks on Satori, MIT’s New Supercomputer
I Programmer: 10th Google Code-in Sets New Records
CustomerThink: Top 10 Machine Learning-as-a-Service Providers 2020
Analytics India: Top 10 Emerging Programming Languages in 2020
Robot Report: Why and How to Run Machine Learning Algorithms on Edge Devices
Analytics India: Why Jupyter Notebooks Are So Popular Among Data Scientists
Julia Blog Posts
Intel Tech.Decoded: New Threading Capabilities in Julia v1.3 (Jameson Nash, Jeff Bezanson and Kiran Pamnany)
Table Logging in Julia (Ole Kröger)
DifferentialEquations.jl v6.11.0: Universal Differential Equation Overhaul (Chris Rackauckas)
Mauve: In Search of a Color (Cormullion)
Tables.jl 1.0 Release (Jacob Quinn)
Collaborating on a Julia Project (Michele Pratusevich)
JuliaLang: The Ingredients for a Composable Programming Language (Lyndon White)
Building an Enigma Emulator and a Bombe (Ole Kröger)
ElectronDisplay.jl v1.0.0 Released
Almost Trivial: Parallelizing a Specialized Matrix Type in Julia (Mayeul d’Avezac)
Google’s Code-In Contest Wrap Up (Avik Sengupta, Dhairya Gandhi and Logan Kilpatrick)
Julia and The Reincarnation of Lisp (Arnuld)
Upcoming Julia Events
Austin: MLSys with Mike Innes (Julia Computing) March 2-4
Boulder: Julia Meetup with Boulder Data Science, Machine Learning and AI March 5
Online: Pharmacology and Pharmacometrics Webinar usingPumas with Vijay Ivaturi March 6
Vancouver: Julia Compiler with Christian Weilbach and Programming in Julia March 12
Münster: Let’s Meet Julia! with Mirko Bunse, Tobias Pfaff and Data Science Meetup Münster March 12
Online: Putting a Trained ML Pipeline Behind a Webserver to Serve It with Dhairya Gandhi (Julia Computing) March 13
Online: Financial Modeling on Large, StreamingDatasets with Josh Day (Julia Computing) March 20
Prague: Machine Learning in Julia with Avik Sengupta (Julia Computing) and Kevin O’Brien at Machine Learning Prague March 20-22
Freiburg: Multiple Dispatch with Konstantinos Michailidis, Aaron Raphael Matthis and Julia User Group Freiburg March 24
Vienna: Revise.jl & Debugging in Julia with Rene Donner and Vienna Julia Meetup March 24
Warsaw: Introduction to Scientific Computing Using the Julia Language with Przemyslaw Szufel, Bogumił Kamiński and Warszawskie Forum Julia March 26
Online: Building and Deploying an NPL Model in Julia with Deepak Suresh (Julia Computing) March 27
Cambridge, UK: Cambridge 4 - A LightGraphs Tour - Flexible Toolkits and Abstractions with Lyndon White and All England Julia User Group April 2
Cape Town: Pharmacometric Modelling & Simulation with Pumas.jl at the World Conference on Pharmacometrics with Vijay Ivaturi and Joga Gobburu April 5-6
Munich: Julia - A Perfect Glue Language with Stephan Sahm and Julia User Group Munich April 8
Online: Intro to Julia with Matt Bauman (Julia Computing) April 15
Vienna: Mathematical Optimisation Modelling in Julia with JuMP.jl with Rene Donner and Vienna Julia Meetup April 20
Online: Intro to Machine Learning and Artificial Intelligence in Julia with Matt Bauman (Julia Computing) April 22
Online: Intro to Parallel Computing in Julia with Matt Bauman (Julia Computing) April 29
Ljubljana: Population Approach Group in Europe (PAGE) with Andreas Noack, Patrick Mogensen, Deepak Vinchhi, Sushil Kumar (Julia Computing) and Vijay Ivaturi June 9-12
London: AI Summit with Avik Sengupta and Sanjeeb Das Gupta (Julia Computing) June 10-11
Louvain-la-Neuve, Belgium: 4th Annual JuMP-dev Workshop June 15-17
Lisbon: JuliaCon 2020 at the ISCTE - Instituto Universitário de Lisboa July 27-31
Denver: American Conference on Pharmacometrics with Andreas Noack, Patrick Mogensen, Deepak Vinchhi, Erik Mayo (Julia Computing) and Vijay Ivaturi October 4-7
Recent Julia Events
Munich: Kickoff with Julia User Group Munich Feb 5
Vienna: Testing & CI for Julia + VScode/Emacs/Vim Tips & Tricks with Rene Donner, Martin Trapp and Vienna Julia Meetup Feb 5
Boulder: Julia Meetup with Boulder Data Science, Machine Learning and AI Feb 6
Online: Introduction to Julia with Dr. Matt Bauman (Julia Computing) Feb 12-13
Vancouver: Kickoff with Tooling with Christian Weilbach and Programming in Julia Feb 13
Vienna: Revise.jl & Debugging in Julia with Rene Donner and Martin Trapp Feb 17
Barcelona: February Julia Get-Together with Adrian Salceanu Feb 18
San Diego: Julia Users and Tools for Oceanography with Gael Forget (MIT) at Ocean Sciences Meeting Feb 18
Online: Introduction to Machine Learning and Artificial Intelligence in Julia with Dr. Matt Bauman (Julia Computing) Feb 19-20
Palma de Mallorca: Julia for Non-Coders with Julia Mallorca Feb 21
Online: Scientific Machine Learning Webinar with Chris Rackauckas Feb 25
Warsaw: O Pakietach w Języku Julia i Zarządzaniu Binarnymi Dependencjami with Przemyslaw Szufel and Bogumił Kamiński Feb 26
Julia Jobs, Fellowships and Internships
Do you work at or know of an organization looking to hire Julia programmers as staff, research fellows or interns? Would your employer be interested in hiring interns to work on open source packages that are useful to their business? Help us connect members of our community to great opportunities by sending us an email, and we’ll get the word out.
There are more than 300 Julia jobs currently listed on Indeed.com, including jobs at Accenture, Airbus, Amazon, AstraZeneca, AT&T, Barnes & Noble, BlackRock, Capital One, CBRE, Charles River Analytics, Citigroup, Comcast, Conde Nast, Cooper Tire & Rubber, Disney, Dow Jones, Facebook, Gallup, Genentech, General Electric, Google, Huawei, Ipsos, Johnson & Johnson, KPMG, Lockheed Martin, Match, McKinsey, NBCUniversal, Netflix, Nielsen, Novartis, OKCupid, Opendoor, Oracle, Pandora, Peapod, Pfizer, Raytheon, Spectrum, Wells Fargo, Zillow, Brown, BYU, Caltech, Dartmouth, Emory, Harvard, Johns Hopkins, Louisiana State University, Massachusetts General Hospital, MIT, Penn State, Princeton, UC Davis, University of Chicago, University of Delaware, University of Kentucky, UNC-Chapel Hill, USC, University of Virginia, Argonne National Laboratory, Federal Reserve Bank, Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, National Renewable Energy Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, State of Wisconsin and many more.
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About Julia and Julia Computing
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and other scientific and numeric computing applications. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. Julia has been downloaded more than 13 million times and is used at more than 1,500 universities. Julia co-creators are the winners of the 2019 James H. Wilkinson Prize for Numerical Software and the 2019 Sidney Fernbach Award. Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, one of the ten largest and most powerful supercomputers in the world.
Julia Computing was founded in 2015 by all the creators of Julia to develop products and provide professional services to businesses and researchers using Julia.
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Julia Computing's mission is to create and deliver products that make Julia easy to use, easy to deploy and easy to scale. We operate out of Boston, London and Bangalore, and we serve customers worldwide.
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