- Your first task is to use California census data to build a model of housing prices in the state.
- This data includes metrics such as the population, median income, and median housing price for each block group in California.
- Block groups are the smallest geographical unit for which the US Census Bureau publishes sample data (a block group typically has a population of 600 to 3,000 people).
- I will call them “districts” for short.
- Your model should learn from this data and be able to predict the median housing price in any district, given all the other metrics.
- The Objective of the business is that your your model’s output (a prediction of a district’s median housing price) will be fed to another machine learning system along with many other signals
- This downstream system will determine whether it is worth investing in a given area. Getting this right is critical, as it directly affects revenue
-
Notifications
You must be signed in to change notification settings - Fork 0
shekinahmanyi/ml_projects
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Projects from Hands on ML with Scikit learn, Keras and Tensorflow - 3rd Edition
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published