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Machine Learning is perhaps the most powerful force in technology, and Python is perhaps the most popular language for doing it. This 2-day workshop helps students understand, build, and interpret machine learning models using the python ecosystem.
This workshop will introduce you to the most important machine learning concepts in a way that’s clear, accessible, and easy to put into action. With no assumed knowledge of Machine Learning, you’ll understand how to think about and interpret Machine Learning problems, and best practices for using the most popular machine learning techniques in a variety of domains.
It starts with the basics of Python’s major data science libraries (Numpy, Pandas, and SciKit Learn), and builds on these to help you implement state-of-the-art machine learning techniques on your own data.
Some familiarity with the core Python programming language is recommended from Introduction to Python Bootcamp or similar experience.
General Assembly’s classes, workshops & events are for recreational purposes and are not regulated by the bureau of proprietary school supervision.
If this class is recorded, students will be sent the recording link within 7 days after class completion by email. Students are encouraged to download and save any shared materials (worksheets, deck if applicable) during class for later reference as they are not be shared by email.
In this workshop you'll learn :
Download Anaconda here prior to class.
Jonathan is a team leader for Kismet Analytics, a full-stack data consulting company that works with companies to build out bespoke data operating systems and improve their analytical capabilities.
His job responsibilities include architecting project strategies, engaging in code reviews, communicating key outcomes to business stakeholders and using the python computing stack for all things analytics: regression, data cleaning, visualization, building data feeds, model deployment and application development.
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