# AI News, Introduction to Python for Data Science: Coding the Naive Bayes Algorithm

## Introduction to Python for Data Science: Coding the Naive Bayes Algorithm

*Save time at check-in by registering for this event via Eventbrite (https://www.eventbrite.com/e/introduction-to-python-for-data-science-coding-the-naive-bayes-algorithm-tickets-37950526045?aff=DS).About the Event:Data scientists need to know how to code, and Python is the most useful and versatile programming language for doing data science.In this practical data science Meetup, you’ll learn foundational skills for adding Python to your data science and analytics toolbox.

What we're doing will work on a Windows machine (Python being multi-platform), but support from our instructor can only be provided for Mac and Linux users.Light snacks will be provided.What You’ll Learn:• How to derive Bayes Theorem and why it's useful• How to derive the Naive Bayes algorithm from Bayes Theorem• How to read data files into Python and pull out simple text features• How to build a Naive Bayes classifier based on our extracted text features• How to evaluate how well our classifier performs in terms of accuracy, precision, recall, f1 score• Which resources you should next utilize to develop your skillsSchedule:6:00 pm – Doors open, Networking & Snacking6:15 pm – Lesson Kickoff, Working with Python6:45 pm – Introduction to supervised machine learning7:15 pm - Introduction to the Naive Bayes algorithm7:45 pm – Coding Naive Bayes in Python, classifying text data9:00 pm – Wrap-Up and Additional ResourcesMeet Your Instructor:Dan Wiesenthal (http://linkedin.com/in/danwiesenthal) holds two degrees from Stanford University, an MS in Computer Science and a BS in Symbolic Systems.

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