After last year’s successful sessions, Patrick Varilly will once again present his glorious notebooks on how to get up and running with Python for Data Scientists. Expect a technical session that you can follow along with or without your own laptop.
In the past few years, Python has emerged as a solid platform for data science. Couple a mature, clean and expressive language with powerful, fully-featured libraries for data wrangling and machine learning, and you’re set up for maximum productivity. Easily ingest your data from practically anywhere using one of Python’s thousands of free libraries.
In detail, we plan to cover the following points:
* Quick history of Python and typical use cases
* Key advantages and disadvantages of Python for data science
* Ways to run python and write code
* Quick tour of the language
* Showcase of useful language packages for data science: NumPy, Matplotlib, SciPy, Pandas, Scikit-learn
* Pointers for further learning