We're delighted to invite you to attend an open session on Thursday 2 May 2019, titled: "Julia & Python: Jumping in Julia.. Why and How?" which will be presented by Eng. Aliaa Rassem, a Senior Data Scientist at Optomatica.
This event is hosted by Nile University and Optomatica.
Python is currently one of top rated popular programming languages. It is a simple, dynamically typed and an object-oriented high-level language. Although Python and R are doing good in wide range of applications, the chances of Julia overtaking them seems to be high over time. Python and Julia share some features however Julia has some more advantages over Python. For example, both Julia and Python utilize parallelism for resource management but Julia is less heavy in terms of the resources that it uses as compared to Python. They both have similar syntax but Julia is yet very powerful. Finally, Julia is faster than Python because it uses both the type declarations and JIT (Just in time) compilation.
Julia offers many useful programming capabilities. It has good concurrency, multiprocessing and distributed computing capabilities. With Julia, You can create hierarchies of types ,use macros that let you manipulate code like data, call libraries written in Python, C, and Fortran and also apply the metaprogramming to generating jula programs from other Julia programs
For data science and machine learning community, Julia introduces powerful libraries for machine learning such as Flux.jl, MLBase.jl, ScikitLearn.jl, MachineLearning.jl, Mocha.jl and TextAnalysis.jl that is far too easy to use than current available python frameworks. It also has best-in-class support for other modern machine learning frameworks such as TensorFlow and MXNet, making it easy to adapt to existing workflows.
In this session, we will go through the features of Julia programming language and show how python and Julia are complementary languages. We will show some code snippets that will take us into Julia world.
Aliaa Rassem is currently a senior data scientist at Optomatica. She received her BSc and MSc degrees in Operations Research & Decision Support from Cairo University. She worked as an Assistant Lecturer at Cairo University in Network Flows, Computational Intelligence, Optimization, Decision Support Methodologists and Mathematics. She also worked as a customer insights consultant at Vodafone. Her research interests include: Machine Learning, Data Modeling and Optimization.
(Room: UB1_Room 116)
Juhayna, Square on 26th of July Corridor, Sheikh Zayed, Giza.
Note: RSVP is a must.
Bring your laptop for rich experience!
For any questions or details, please contact us through PyData-Cairo Meetup Messages/discussion board, or Nile University contacts