Главная
Study mode:
on
1
Introduction
2
Competition Page
3
Loading the Starter Notebook
4
Training Dataset Description
5
Test Dataset
6
Distribution of Target Variable
7
Defining Cross Validation Scheme
8
Feature Engineering
9
Test and Out of Fold Dataframe
10
Model Training Loop
11
Training the Model
12
Evaluating out of fold score
13
Feature Importance
14
Create Submission
15
Checking the Leaderboard and Conclusion
Description:
Explore a comprehensive walkthrough of a Kaggle competition starter notebook in this 26-minute video tutorial by Kaggle Grandmaster Rob Mulla. Learn how to approach the PogChamps community challenge, focusing on predictive modeling and Python coding. Discover techniques for feature creation, cross-validation, and building a LightGBM model. Follow along as Rob guides you through loading the starter notebook, analyzing training and test datasets, defining cross-validation schemes, and performing feature engineering. Gain insights into model training, evaluating out-of-fold scores, and interpreting feature importance. Conclude by creating a submission and checking the competition leaderboard. Access additional resources, including the competition link, live coding streams, and related tutorials on pandas and exploratory data analysis.

Kaggle Competition Starter Notebook Walkthrough

Rob Mulla
Add to list
0:00 / 0:00