- 2.1 Car price prediction project
- 2.2 Data preparation
- 2.3 Exploratory data analysis
- 2.4 Setting up the validation framework
- 2.5 Linear regression
- 2.6 Linear regression: vector form
- 2.7 Training linear regression: Normal equation
- 2.8 Baseline model for car price prediction project
- 2.9 Root mean squared error
- 2.10 Using RMSE on validation data
- 2.11 Feature engineering
- 2.12 Categorical variables
- 2.13 Regularization
- 2.14 Tuning the model
- 2.15 Using the model
- 2.16 Car price prediction project summary
- 2.17 Explore more
- 2.18 Homework
Did you take notes? You can share them here (or in each unit separately)
- Notes from Kwang Yang
- Notes from Sebastián Ayala Ruano
- Notes from Ayoub Berdeddouch
- Notes from Alvaro Navas
- Notes from froukje
- Notes from Jon Areas
- Notes from Memoona Tahira
- Notes from Wesley Barreto
- Notes from Hareesh Tummala
- Notes from Anneysha Sarkar
- Notes from Peter Ernicke
- Notes from Marcos Benício
- Notes from Oscar Garcia
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