Newsletter – February 2018

  1. Parallel Computing with JuliaBox
  2. Julia Computing’s Artificial Intelligence and Machine Learning Capabilities
  3. Live Julia Training on YouTube Feb 6 – Introduction to Solving Differential Equations with Chris Rackauckas
  4. JuliaCon 2018 Call for Proposals
  5. JuliaCon 2018 Mentorship for First-Time Speakers
  6. JuliaCon 2018 Call for Corporate Sponsors
  7. MSRIT Machine Learning and Artificial Intelligence Training Using Julia
  8. Hyperion Research Honors Celeste Team, Including Julia Computing, With HPC Innovation Award
  9. Julia Computing’s Keno Fischer and NERSC’s Prabhat Discuss Celeste on Ad Astra Podcast
  10. Julia Computing’s Alan Edelman and Viral Shah Discuss Machine Learning in Factor Daily
  11. Julia Computing’s Alan Edelman and Viral Shah Discuss Deep Learning with iSPIRIT in Bangalore
  12. Irán Román’s Artificial Intelligence with Neural Networks Course Using Julia (en Español)
  13. Julia Jobs, Fellowships and Internships
  14. Julia Meetup Groups
  15. Recent Julia Blog Posts
  16. Upcoming Julia Events
  17. Recent Julia Events
  18. Contact Us

1. Parallel Computing with JuliaBox:

JuliaBox is now available at scale with parallel computing capabilities. JuliaBox runs in the cloud on dozens, hundreds or thousands of nodes, depending on your requirements. As always, there is no download required with JuliaBox – you can run it straight from your browser using a Jupyter notebook. Full JuliaBox documentation including examples and reference information for parallel functionality is available here. For pricing, a free 2 week trial, or more information about parallel computing with JuliaBox, please contact us and let us know how many nodes you require.

The free version of JuliaBox continues to be fully supported for current and new users with the latest version of Julia, package updates, new features and improved memory, flexibility and reliability.

2. Julia Computing’s Artificial Intelligence and Machine Learning Capabilities:

Julia Computing continues to undertake a number of innovative consulting and custom development projects involving artificial intelligence, machine learning and deep learning. Julia’s machine learning capabilities are integrated with JuliaDB, making it possible to ingest data from a variety of sources, apply machine learning and generate insights quickly. Julia Computing employs many of the core developers of Julia and its machine learning packages. Please contact us if you are interested in partnering with Julia Computing on projects involving artificial intelligence, machine learning or deep learning.

Examples include:

Celeste: Julia Computing partnered with the National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory, UC Berkeley, MIT Julia Lab and Intel to classify 188 million astronomical objects in just 14.6 minutes using one of the ten largest and most powerful supercomputers in the world.

Path BioAnalytics: Julia Computing and Path BioAnalytics are using deep learning and image processing techniques to identify organoids for precision medicine.

Drishti Eye Hospitals: Julia Computing partnered with Drishti Eye Hospitals and developed a deep learning algorithm to diagnose diabetic retinopathy, which affects more than 126 million patients worldwide.

Please see our Case Studies for many other examples of how Julia can be used to solve challenges you face.

3. Live Julia Training on YouTube Feb 6: 

Introduction to Solving Differential Equations with Chris Rackauckas: Please join Chris Rackauckas and Julia Computing for a live YouTube training on Solving Differential Equations in Julia Tuesday Feb 6 at 10 am PST / 1 pm EST / 6 pm GMT / 7 pm CET / 11:30 pm IST.

4. JuliaCon 2018 Call for Proposals:

JuliaCon is coming to University College London Aug 7-11, 2018.

Everyone who is interested is strongly encouraged to submit a proposal, regardless of level of experience with Julia or as a speaker. JuliaCon thrives on having talks ranging from introductory to advanced. If you are reading this and work with Julia in any form, you are encouraged to submit a proposal.

Proposals may be submitted for talks, lightning talks, workshops, posters and package collaboration. Other ideas and suggestions, such as a topic or focus for a hackathon, are also welcome. Please click
here for more details, proposal advice and submission.

5. JuliaCon 2018 Mentorship for First-Time Speakers: 

If you are willing to mentor a first-time speaker including providing feedback on abstracts or presentations, discussing presentation skills and more, please sign up here.

JuliaCon 2018 offers mentorship for first-time speakers and presenters. Details are available here. Please indicate in your proposal submission if you would be interested in mentorship.

6. JuliaCon 2018 Call for Corporate Sponsors:

JuliaCon 2018 has corporate sponsorship opportunities available. JuliaCon 2018 will be held Aug 7-11, 2018 at University College London.

7. MSRIT Machine Learning and Artificial Intelligence Training Using Julia:

Julia Computing led a 5-day training at Bangalore’s M.S. Ramaiah Institute of Technology in machine learning and artificial intelligence using Julia. The training was extremely successful and one of many to come in India, the US and worldwide.

8. Hyperion Research Honors Celeste Team, Including Julia Computing, With HPC Innovation Award:

Julia Computing was part of the Celeste team that was awarded the HPC Innovation Award by Hyperion Research. The Celeste team leveraged 650,000 cores with 1.3 million threads to analyze 56 terabytes of data and classify 188 million astronomical objects in 14.6 minutes using one of the ten largest and most powerful supercomputers in the world.

9. Julia Computing’s Keno Fischer and NERSC’s Prabhat Discuss Celeste on Ad Astra Podcast:

Julia Computing’s Keno Fischer and NERSC’s Prabhat participated in a podcast interview on Ad Astra about Celeste. Tune in to hear how the Celeste team classified 188 million astronomical objects in just 14.6 minutes.

10. Julia Computing’s Alan Edelman and Viral Shah Discuss Machine Learning in Factor Daily:

Julia Computing co-founders Alan Edelman (Julia Computing Chief Scientist and MIT Professor of Applied Mathematics) and Viral Shah (Julia Computing CEO) were interviewed by Factor Daily. Alan explains: “We can take machine learning everywhere but it’s not going to be one size fits all.”

11. Julia Computing’s Alan Edelman and Viral Shah Discuss Deep Learning with iSPIRIT in Bangalore:

Alan Edelman and Viral Shah joined Chintan Mehta at iSPIRIT to discuss deep learning. The event was streamed live on YouTube.

12. Irán Román’s Artificial Intelligence with Neural Networks Course Using Julia (en Español):

Stanford University’s Irán Román published a course in Spanish on artificial intelligence with neural networks using Julia: “Algoritmos de Inteligencia Artificial con Redes Neuronales Artificiales.

13. Julia Jobs and Internships

Do you work at or know of an institution 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 200 Julia jobs currently listed on Indeed.com, including jobs at Google, Facebook, IBM, KPMG, Ernst & Young, Booz Allen Hamilton, Comcast, Zulily, National Renewable Energy Research Laboratory, Los Alamos National Laboratory, Brown, Princeton, Columbia, Notre Dame, MIT, University of Chicago and many more.

14. Julia Meetup Groups:

There are 26 Julia Meetup groups worldwide with more than 5 thousand members. If there’s a Julia Meetup group in your area, we hope you will consider joining, participating and helping to organize events. If there isn’t, we hope you will consider starting one.

15. Recent Julia Blog Posts

16. Upcoming Julia Events

17. Recent Julia Events:

18. Contact Us

Please contact us if you wish to:

  • Purchase or obtain license information for Julia products such as JuliaPro, JuliaPro Enterprise, JuliaRun, JuliaDB, JuliaFin or JuliaBox
  • Obtain pricing for Julia consulting projects for your organization
  • Schedule Julia training for your organization
  • Share information about exciting new Julia case studies or use cases
  • Spread the word about an upcoming conference, workshop, training, hackathon, meetup, talk or presentation involving Julia
  • Partner with Julia Computing to organize a Julia meetup, conference, workshop, training, hackathon, talk or presentation involving Julia
  • Submit a Julia internship or job posting

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 many other domains. 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. For example, Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, the world’s sixth-largest supercomputer. With more than 1.8 million downloads and +101% annual growth, Julia is one of the top programming languages developed on GitHub. Julia adoption is growing rapidly in finance, insurance, machine learning, energy, robotics, genomics, aerospace, medicine and many other fields.

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. Julia Computing offers the following products:

  • JuliaPro for data science professionals and researchers to install and run Julia with more than one hundred carefully curated popular Julia packages on a laptop or desktop computer.
  • JuliaRun for deploying Julia at scale on dozens, hundreds or thousands of nodes in the public or private cloud, including AWS and Microsoft Azure.
  • JuliaFin for financial modeling, algorithmic trading and risk analysis including Bloomberg and Excel integration, Miletus for designing and executing trading strategies and advanced time-series analytics.
  • JuliaDB for in-database in-memory analytics and advanced time-series analysis.
  • JuliaBox for students or new Julia users to experience Julia in a Jupyter notebook right from a Web browser with no download or installation required.

To learn more about how Julia users deploy these products to solve problems using Julia, please visit the Case Studies section on the Julia Computing Website.

Julia users, partners and employers hiring Julia programmers in 2018 include Amazon, Apple, BlackRock, Booz Allen Hamilton, Capital One, Comcast, Disney, Ernst & Young, Facebook, Ford, Google, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC, Uber, and many more.