Machine Learning in Python: How to Fit a Random Forest in Five Minutes | Thomas Laetsch
This is an introductory class on Machine Learning with Python by our Instructor Thomas Laetsch.
In this short course we will cover the basics of decision trees and bootstrapping, and from there get into random forests -- one of the big success stories in machine learning, useful for predictive tasks in both classification and regression problems. By the end of this video, you will get a basic understanding of the bias-variance trade-off, and how random forest models help us navigate through these troubled waters.
To take advantage of the hands-on portions of the lecture, it is recommended that students have installed Anaconda with Python 3.7 from https://www.anaconda.com/distribution/
About Us: NYC Data Science Academy is a proprietary school that offers immersive in-person and online data science bootcamps, professional courses and corporate offerings specializing in all fields of #datascience. We designed the Data Science Bootcamp to provide accelerated training along with life-long jo support and full-financing options. The objective of the Data Science Bootcamp is to provide training in most of the data science tools and methods that prepare students for employment opportunities across all industries as data science professionals.
Immersive Data Science Bootcamp (NYC): https://nycdatascience.com/data-scien... Online Data Science Bootcamp: https://nycdatascience.com/online-dat...
For all professional development course information, visit https://nycdatascience.com/
If you have any questions about applications and enrollment, please email [email protected].