How to validate data science models: Lessons from Covid19. Data Science The Missing Pieces DSTMP7
Channel: Kaiser Fung - Principal Analytics Prep
Date: 2020-04-02

Data scientists learn from historical datasets by building "models". The value of such models is its ability to explain other similar datasets. A fundamental principle of model-building is to use a validation dataset to judge the accuracy of the model. How this works is explained in textbooks but hard to grasp unless you encounter a real-life example. In this video, I use a recent exploratory analysis of Covid-19 data from Lombardia, the epicenter of Italy's epidemic, to demonstrate why some models will explain the past well but fail to predict the future. #datascience #backtesting #validation #models #analytics #principalanalyticsprep

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Other episodes:
DSTMP#1 What You Need to Know about Functions for Data Science
https://youtu.be/XTWCWPVAl5c
DSTMP#2 How to make a Good Chart (without fancy tools)
https://youtu.be/3ju3tD8tCV8
DSTMP#3 Not Statistically Significant
https://youtu.be/Zk6m5H-SOTc
DSTMP#6 How to Standardize Data
https://youtu.be/HOqh-Gz7lJI
Also,
FUNG WITH DATA: revealing secrets of how data, software, and algorithms affect everyone
https://www.youtube.com/playlist?list=PLSWpubLXmle-ikEP7XVcCDKtnPo6GUFz0