This course covers the essential varieties of machine studying algorithms, resolution strategies primarily based on the specifics of the issue you are attempting to resolve, in addition to the traditional machine studying workflow.
As Machine Studying explodes in recognition, it’s turning into ever extra essential to know exactly tips on how to body a machine studying mannequin in a way applicable to the issue we try to resolve, and the info that we have now out there.
On this course, Creating Machine Studying Fashions you’ll achieve the power to decide on the correct sort of mannequin in your downside, then construct that mannequin, and consider its efficiency.
First, you’ll learn the way rule-based and ML-based methods differ and their strengths and weaknesses and the way supervised and unsupervised studying fashions differ from one another.
Subsequent, you’ll uncover tips on how to implement a spread of strategies to resolve the supervised studying issues of classification and regression. You’ll achieve an intuitive understanding of the the mannequin algorithms you should use for classification and regression. Lastly, you’ll spherical out your information by constructing clustering fashions utilizing a few completely different algorithms, and validating the outcomes.
While you’re completed with this course, you should have the talents and information to establish the proper machine studying downside setup, and the suitable resolution and analysis strategies in your use-case.
In regards to the writer
An issue solver at coronary heart, Janani has a Masters diploma from Stanford and labored for 7+ years at Google. She was one of many unique engineers on Google Docs and holds four patents for its real-time collaborative enhancing framework.
Created by: Janani Ravi
Up to date: Oct 29, 2019
Length: 2h 44m
Size: 390.87 MB