This is the Day 12 of Kaggle's 30 Days of ML Challenge where you can learn Machine Learning (based onThis is the Day 11 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:
???? What You’ll Learn
In Lesson 1 (Introduction), you’ll learn more about what the course covers.
Most machine learning libraries (including scikit-learn) give an error if you try to build a model using data with missing values. In Lesson 2 (Missing Values), you’ll learn about three different approaches for dealing with missing values in your data.
A categorical variable is a variable that takes only a limited number of values, and it’s common to encounter them in data. Learn how to work with them in Lesson 3 (Categorical Variables).
Tutorial 1 - https://www.kaggle.com/alexisbcook/introduction
Exercise 1 - https://www.kaggle.com/kernels/fork/3370272
Tutorial 2 - https://www.kaggle.com/alexisbcook/missing-values
Exercise 2 - https://www.kaggle.com/kernels/fork/3370280
Tutorial 3 - https://www.kaggle.com/alexisbcook/categorical-variables
Exercise 3 - https://www.kaggle.com/kernels/fork/3370279
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
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