Datasets:
- 001_Forbes
- 002_Titanic
- 003_Love
- 004_Taxi
- 005_NYC
- 006_London
- 007_Fifa
- 008_Tornados
- 009_Central
- 010_ECommerce
- 011_SF
- 012_Heart
- 013_Roller
- 014_Airbnb
- 015_Food
- 016_Holiday
- 017_Hacker
- 018_Staff
- 019_Aircraft
- 020_Real
- 021_Telco
- 022_Airbnbs
- 023_Climate
- 024_Salary
- 025_Data
- 026_Predicting
- 027_Supermarket
- 028_Predict
- 029_NYTimes
- 030_Professionals
- 031_Trustpilot
- 032_Delicatessen
- 033_Employee
- 034_World
- 035_Billboard
- 036_US
- 037_Ted
- 038_Stroke
- 039_Happy
- 040_Speed
- 041_Airline
- 042_Predict
- 043_Predict
- 044_IMDb
- 045_Predict
- 046_120
- 047_Bank
- 048_Data
- 049_Boris
- 050_ING