Join us for this machine learning course demo that will cover the basics of decision trees and bootstrapping, and then get into random forests.
This is an introductory lesson on Machine Learning with Python by NYC Data Science Academy Instructor Thomas Laetsch. The course demo will feature basic coding techniques that will help you to fit a random forest in five minutes.
In this short course we will cover the basics of decision trees and bootstrapping, and from there we will get into random forests -- one of the big success stories in machine learning. This is useful for predictive tasks in both classification and regression problems. Attendees will leave with a basic understanding of the bias-variance trade-off, and learn how random forest models help us to navigate through these troubled waters.
Both, programmers who are looking to expand their data toolkit and non-programmers who do not have any coding experience, are invited to join. To take advantage of the hands-on portions of the lecture, it is recommended that students have installed Anaconda with Python 3.7.
This session will also include a brief overview of the NYC Data Science Academy, including its data science bootcamp and other course offerings.
What to expect:
In the first part of the info session, we will give you an overview of what makes NYC Data Science Academy different. You will learn how to prepare for the Bootcamp, what to learn, and application process.
The session will be as follows:
7:00 - 7:10 pm Introduction to NYC Data Science Academy and What We Do
7:10 - 7:45 pm Machine Learning with Python by Thomas Laetsch
7:45 - 8:00 pm Q&A & Mingling
NYC Data Science Academy
500 8th Avenue, Suite 905, New York, NY 10018
Save your spot → https://www.eventbrite.com/e/free-course-demo-hands-on-machine-learning-in-python-tickets-81795086305