I am working at Safran as a research engineer. My major responsibility in the company is analyzing data obtained from airplanes and helicopters using various statistical models and machine-learning algorithms.
Formerly, I worked at Samsung Electronics in South Korea for 3 years as a senior engineer. At Samsung, I have developed various computer networking related algorithms and software for smartphones and IoT devices to improve user experiences.
Before joining Samsung, I finished my Ph.D. at Pohang University of Science and Technology (POSTECH) in South Korea. The theme of my thesis was "Traffic Engineering in Data Center Networks using Software Defined Networking."
A Jupyter notebook is quite handy for rapid REPL (Read-Eval-Print-Loop) style tasks
such as exploratory data analysis and data science. However, we would feel
deficiencies in proper SW engineering supports at some point as the notebook grows
to have larger and more complicated code. It is because the Jupyter notebook lacks
several important features including code sharing, refactoring support,
version control and advanced editing. Fortunately, traditional full-fledged IDEs,
such as VS Code or PyCharm, are available at hand and they support
these lacking features very well.
Then, why don’t we take advantage of the best of both worlds?
In this beginner-level hands-on talk, I will demonstrate how to
transform Jupyter notebook workflows to a proper Python package using VS Code.
I will also introduce several basic but essential refactoring recommendations.
By doing so, you can use the package for several notebooks
and even share with your colleagues and friends.