Alexander Binun

Useful tool in my machine learning activities (esp. prediction) as it supports build-in modules like Neural Nets and many math primitives. In addition I can always link C or Java modules to my Matlab software.

During the recent 20 years of my "software development" life I dealt with various high-level languages like Matlab - but always got back to the roots. "Roots" are C, C++. Sometimes you should add a plugin to Matlab or write a kernel module in Linux (to accelerate data processing).

Useful for developing GUI when it comes to simulating the system. A distributed system with (possibly crashing) computers and rich animations is easily depicted in Delphi.

An universal engine that, along with C++, helps in algorithm design as it supports a lot of data structures.

As a Data Science researcher , I have to store statistics into a DB. MSSQL is a open source DB which helped me a lot - in addition, it offers API to high variety of languages, incl. my favourites C and C++.

As a Data Science researcher , I have to store statistics into a DB. MSSQL is a open source DB which helped me a lot - in addition, it offers API to high variety of languages, incl. my favourites C and C++.

One of fields I am familiar with is Distributed Systems; these include processing of big amounts of data using Hadoop and Zookeeper.

I started playing with Python when researching Distributed Clouds (OpenStack was an example). Now Python , in addition to Matlab, is my Big Data language. Last but not least - it is free (unlike Matlab).

I am developing algorithms during the recent 10 years as I am active in R&D fields. The algorithms include mostly various machine learning techniques and graph-based algorithms.