Kaggle 30 Days of ML (Day 14) - XGBoost, Data Leakage - Learn Python ML in 30 Days

This is the Day 14 of Kaggle's 30 Days of ML Challenge where you can learn Machine Learning (based on Python) in 30 days (Kind of). It's not a competition but a challenge to make a habit of coding ML every day. If you haven't registered for the Kaggle Challenge Don't worry, You can follow along my videos every day.

From Kaggle Email:
In Lesson 6 (XGBoost), you will learn how to build and optimize models with gradient boosting. This method dominates many Kaggle competitions and achieves state-of-the-art results on a variety of datasets.

In Lesson 7 (Data Leakage), you will learn what data leakage is and how to prevent it. If you don't know how to prevent it, leakage will come up frequently, and it will ruin your models in subtle and dangerous ways. So, this is one of the most important concepts for practicing data scientists.

This marks the end of Kaggle's Intermediate ML Course

XGBoost Tutorial 1 - https://www.kaggle.com/alexisbcook/xgboost
Exercise 1 - https://www.kaggle.com/kernels/fork/3370271

XGBoost Tutorial from StatQuest with Josh Starmer - https://www.youtube.com/watch?v=OtD8wVaFm6E

Data Leakage 2 - https://www.kaggle.com/alexisbcook/data-leakage
Exercise 2 - https://www.kaggle.com/kernels/fork/3370270

Courtesy: Kaggle Learn

Related Videos:
Day 1 - https://youtu.be/gZ8hD9MpQyo
Day 2 - https://www.youtube.com/watch?v=KxBhF-uxOD0
Day 3 - https://www.youtube.com/watch?v=yHOqH7GSfW0
Day 4 - https://youtu.be/Dq72Ng3Cc4Y
Day 5 Part 1 - https://www.youtube.com/watch?v=duquxFeqsiE
Day 5 Part 2 - https://www.youtube.com/watch?v=3RZfILSG7Is
Kaggle Introduction Walkthrough to get you started with Data Science - Webinar
- https://youtu.be/sstKQYgZRPo
#kaggle #30daysofml #machinelearning #datascience

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