Scala, Go-Lang, Julia, Python... Which should one use, and why?

Starting a new data-science / machine learning project?
Rewriting an existing project?
Considering which language to use?

During the last few years, besides the classical Java / C# / C++ etc, new languages had emerged.
In this meetup, we will discuss the advantages (and disadvantages) of Scala, GoLang and Julia, compared to Java, C#, Python, etc.

Zoltan C. Toth, founder and CTO of Datapao, will come to Vienna to discuss in his talk:

Choosing the best language and format for real-time Industry 4.0 applications.

In Industry 4.0 and IoT applications high-performance real-time data analysis is essential.
A few questions arise:

• Which language do you use if you want to create a high-performant streaming data application?
• Which data format should you use if you want to have both data verification and performance?

I’ll share some of the benchmarks we did interally at Datapao when we faced the challenge of deciding Go vs Python and JSON vs Avro.

Zoltan C. Toth
@zoltanctoth
http://linkedin.com/in/zoltanctoth

Zoltan is founder and CTO of Datapao, an Industry 4.0 Data Architecture Consultancy. He is also a Senior Instructor and Consultant for Databricks, the company founded by the creators of Apache Spark. Earlier he led the Data Engineering department at Prezi.

In addition, we will host 2 speakers from ContextFlow:

Florian has a degree in Computer Visualistics and also received a Phd while working for 12 years as a research at the VRVis Reseach Center in the Bio-Medical Visualization group. He now focuses on system engineering at contextflow. He will explain why they have chosen GoLang for the backend as well as the obstacles they have encountered and how they have solved them

With a background in electrical engineering René has worked for 8 years at the Medical University Vienna as a researcher in computer vision, focusing on anatomical structure localization and content based image retrieval. He is now CTO at contextflow, applying deep learning to large scale medical image data and developing smart tools to aid radiologists in their challenging tasks. He will demonstrate how Julia is faster than Python when it comes to real-time Machine Learning in general, and in particular Neural Networks and Deep Learning models

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