The dataset consists of the following files and folders:

train.csv: This file contains the training data, including features and the target variable (log permeability).
test.csv: This file contains the test data, which includes the features for which you need to predict the log permeability.
sample_submission.csv: This file provides the format required for submitting your predictions for the test set.
images/: This folder contains the images associated with each sample in the dataset.
train.csv
The train.csv file includes the following columns:

ID: Unique identifier for each sample.
feature_1, feature_2, ..., feature_n: Various features that describe the geological properties of the sample.
Log Permeability: The target variable representing the logarithm of the permeability of the sample.
test.csv
The test.csv file includes the following columns:

ID: Unique identifier for each sample.
feature_1, feature_2, ..., feature_n: Various features that describe the geological properties of the sample.
sample_submission.csv
The sample_submission.csv file includes the following columns:

ID: Unique identifier for each sample in the test set.
Log Permeability: The predicted logarithm of the permeability for each sample.
images/
The images/ folder contains the images associated with each sample. The naming convention for the images corresponds to the ID of each sample, ensuring that each image can be uniquely linked to its respective sample in the train.csv and test.csv files.