THIS TUTORIAL HAS REQUIREMENTS AND INSTRUCTIONS LISTED BELOW
Python is quickly becoming the go-to language for data analysis. However, there are so many tools out there that it can be difficult to figure out which ones are useful. In this workshop, I’ll give you an in-depth look at some of the best tools for data wrangling, machine learning, and data visualization. You’ll learn strategies for working with data, how to structure a data analysis workflow, and which tools are appropriate for handling different kinds of data. You’ll leave with a good understanding of different data analysis techniques in Python.
Using Pandas, Scikit-Learn, and matplotlib, we’ll work through a data analysis workflow from start to finish, and we’ll cover the following data analysis problems:
TUTORIAL REQUIREMENTS AND INSTRUCTIONS FOR ATTENDEES
* A basic understanding of Python is necessary, but knowledge of the tools is not.
* Pandas, Scikit-Learn, and matplotlib are the tools we’ll be working with in Python. They can easily be installed with a distribution (such as Anaconda). I’ll post all of the materials to my Github account, so having a Github account would be helpful.
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Sarah is a data scientist at Reonomy, where she’s helping to build disruptive tech in the commercial real estate industry in New York City. Three of her favorite things are Python, data, and machine learning.
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