Copenhagen, Denmark – Danske Bank, Denmark’s largest bank, announced that JuliaPro will be available on Microsoft Azure’s Data Science Virtual Machine (DSVM) for participants in the Business Analytics Challenge 2017.
The Business Analytics Challenge 2017 is sponsored by Danske Bank, Microsoft and KMD. The competition is open to all undergraduate and master’s degree students in Denmark and the first prize is 75 thousand kroner. Registration is open until March 31.
This announcement comes two months after the release of JuliaPro and one month after JuliaPro launched on Microsoft Azure’s Data Science Virtual Machine (DSVM).
Viral Shah, Julia Computing CEO says, “We are thrilled that Julia adoption is accelerating so rapidly during the first quarter of 2017. In the last three months, we introduced the new JuliaPro and launched it on the world’s two largest cloud environments: Amazon’s AWS and Microsoft Azure’s Data Science Virtual Machine (DSVM). Julia Computing wishes the best of luck to all contestants in the Danske Bank Business Analytics Challenge 2017.”
About Julia Computing and Julia
Julia Computing (JuliaComputing.com) was
founded in 2015 by the co-creators of the Julia language to provide
support to businesses and researchers who use Julia.
Julia is the fastest modern high performance open source computing language for data and analytics. It combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of Java and C++. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity.
Julia is lightning fast. Julia provides speed improvements up to
1,000x for insurance model estimation, 225x for parallel
supercomputing image analysis and 11x for macroeconomic modeling.
Julia is easy to learn. Julia’s flexible syntax is familiar and
comfortable for users of Python, R and Matlab.
Julia integrates well with existing code and platforms. Users of
Python, R, Matlab and other languages can easily integrate their
existing code into Julia.
Elegant code. Julia was built from the ground up for
mathematical, scientific and statistical computing, and has advanced
libraries that make coding simple and fast, and dramatically reduce
the number of lines of code required – in some cases, by 90%
Julia solves the two language problem. Because Julia combines
the ease of use and familiar syntax of Python, R and Matlab with the
speed of C, C++ or Java, programmers no longer need to estimate
models in one language and reproduce them in a faster
production language. This saves time and reduces error and cost.
Employers looking to hire Julia programmers in 2017 include: Google, Apple, Amazon, Facebook, IBM, BlackRock, Capital One, PricewaterhouseCoopers, Ford, Oracle, Comcast, Massachusetts General Hospital, NaviHealth, Harvard University, Columbia University, Farmers Insurance, Pilot Flying J, Los Alamos National Laboratory, Oak Ridge National Laboratory and the National Renewable Energy Laboratory.
Julia users and partners include: Amazon, IBM, Intel, Microsoft, DARPA, Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Federal Aviation Administration (FAA), MIT Lincoln Labs, Moore Foundation, Nobel Laureate Thomas J. Sargent, Federal Reserve Bank of New York (FRBNY), Capital One, Brazilian National Development Bank (BNDES), BlackRock, Conning, Berkery Noyes, BestX, Path BioAnalytics, Invenia, AOT Energy, AlgoCircle, Trinity Health, Gambit, Augmedics, Tangent Works, Voxel8, UC Berkeley Autonomous Race Car (BARC) and many of the world’s largest investment banks, asset managers, fund managers, foreign exchange analysts, insurers, hedge funds and regulators.
Universities and institutes using Julia include: MIT, Caltech, Stanford, UC Berkeley, Harvard, Columbia, NYU, Oxford, NUS, UCL, Nantes, Alan Turing Institute, University of Chicago, Cornell, Max Planck Institute, Australian National University, University of Warwick, University of Colorado, Queen Mary University of London, London Institute of Cancer Research, UC Irvine, University of Kaiserslautern.
Julia is being used to: analyze images of the universe and research dark matter, drive parallel computing on supercomputers, diagnose medical conditions, provide surgeons with real-time imagery using augmented reality, analyze cancer genomes, manage 3D printers, pilot self-driving racecars, build drones, improve air safety, manage the electric grid, provide analytics for foreign exchange trading, energy trading, insurance, regulatory compliance, macroeconomic modeling, sports analytics, manufacturing and much, much more.
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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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