Back to Meaningful Predictive Modeling
University of California San Diego

Meaningful Predictive Modeling

This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better? By the end of this course you will be familiar with diagnostic techniques that allow you to evaluate and compare classifiers, as well as performance measures that can be used in different regression and classification scenarios. We will also study the training/validation/test pipeline, which can be used to ensure that the models you develop will generalize well to new (or "unseen") data.

Status: Data Preprocessing
Status: Natural Language Processing
IntermediateCourse9 hours

Featured reviews

PT

5.0Reviewed Mar 31, 2021

The course provided a lot of insights into predictive modeling.

NS

4.0Reviewed Nov 16, 2019

Excellent content, but presentation is a bit challenging at times.

All reviews

Showing: 10 of 10

surendar ramamoorthy
2.0
Reviewed Jun 29, 2019
Padam Jung Thapa
5.0
Reviewed Mar 31, 2021
SNIGDHA KHANNA
5.0
Reviewed May 7, 2021
ANUSHREE CHAKRABORTY
5.0
Reviewed Mar 24, 2021
oriol pi
5.0
Reviewed Sep 16, 2019
韓. 彬
5.0
Reviewed Jan 3, 2026
Sudhananda Pal
5.0
Reviewed Apr 14, 2021
Neil Shrubak
4.0
Reviewed Nov 17, 2019
J Nahshon Bright Patten
4.0
Reviewed Jun 30, 2020
SANTIAGO ORTIZ CEBALLOS
3.0
Reviewed Jul 5, 2020