Conteúdo do Curso
Principal Component Analysis
Principal Component Analysis
Challenge
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tudo estava claro?
Challenge
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tudo estava claro?
Challenge
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.
Tudo estava claro?
Tarefa
The task is to process the dataset and create a principal component analysis model with 3 components.
- Load the
train.csv
(from web) dataset. - Drop the
'Id'
column. - Drop columns that contain
NaN
values. - Standardize the dataset.
- Create a PCA model with 3 components for the dataset.