The Kaggle Intermediate Machine Learning course provides essential skills to handle common challenges in real-world datasets, such as missing values, non-numeric data, and data leakage.
The course covers the use of pipelines for preprocessing and deploying complex models, cross-validation for better model testing, and XGBoost for accurate modeling of structured data.
Building on the Intro to Machine Learning and Pandas courses, this course prepares learners for advanced topics like Feature Engineering and Time Series analysis.
It offers practical exercises and tutorials, all free of cost, under the instruction of Alexis Cook, and takes an estimated four hours to complete.
Certificate Link: https://github.com/NiharJani2002/kaggle-Intermediate-Machine-Learning/blob/master/Nihar%20Jani%20-%20Intermediate%20Machine%20Learning.png
![image](https://private-user-images.githubusercontent.com/84491997/350103771-b91483a4-bcea-4f3e-b17e-59179e72817d.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.p2cTHrGzUUXXfeLKvRHqr33G22y-8Ae4UkxiPwFyg5I)