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Performing regression tasks using decision tree & PCA basics

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In this 1-hour long project-based course, you will learn how to perform regression tasks using decision tree & some PCA fundamental coding. you will get expertise in acing following tasks- Predicting two decision tree regression model Drawing Decision tree for regression Regularize a decision tree regressor Setting up the environment for dimensional reduction Coding for Projection methods in Dimensionality reduction Coding for PCA using SVD decomposition and SCIKIT learn

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Enhance your data science skills with the focused course "Performing Regression Tasks Using Decision Tree & PCA Basics," offered by Coursera. This intermediate-level, project-based course is designed to be completed in just one hour, making it a concise yet powerful learning experience. Throughout the course, you will delve into the application of decision trees for regression tasks and understand the fundamentals of Principal Component Analysis (PCA) through practical coding exercises. Best of all, it's available for free, providing an accessible opportunity for those looking to expand their personal development in the field of data science. Ideal for learners with some prior knowledge in the domain, this course will help you solidify your understanding and apply it to real-world scenarios.