2022-07-23 –, Green
This session has moved to Zoom. Please join with Zoom ID: 6376486897 at 2PM Israel time.
This (Hebrew language) workshop provides an introduction to the Julia language for machine learning engineers, data-scientists, and statisticians. Attendees will gain a solid entry point for using Julia as their preferred data analysis tool.
This Juliacon 2022 workshop in Hebrew (עברית) is aimed at data-scientists, machine learning engineers, and statisticians that have experience with a language like Python or R, but have not used Julia previously. In learning to use Julia, a contemporary "stats based" approach is taken focusing on short scripts that achieve concrete goals. This is similar to the approach of the Statistics with Julia book.
The primary focus is on statistical applications and packages. The Julia language is covered as a by-product of the applications. Thus, this workshop is much more of a how to use Julia for stats course than a how to program in Julia course. This approach may be suitable for statisticians and data-scientists that tend to do their day-to-day scripting with a data and model based approach - as opposed to a software development approach.
An extensive Jupyter notebook for the workshop together with data files is here. You can install it to follow along. The Jupyter notebook is not in Hebrew.
If you don't already have Julia with IJulia (Jupyter) installed, you can follow the instructions in this video. It is recommended that you have Julia 1.7.3 or higher installed.
Associate Professor Yoni Nazarathy from the University of Queensland Australia, specializes in data science, probability and statistics. His specific research interests include scheduling, control, queueing theory, and machine learning. He has been at The University of Queensland for over a decade, teaching courses in the Masters of Data Science program and working on research. Prior to his previous academic positions in Melbourne and the Netherlands, he worked in the aerospace industry in Israel. He is the co-author of a data science book, Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence as well as an ongoing book with drafts available The Mathematical Engineering of Deep Learning.