SNSDE-011 JAV By the end of this module, participants will be able to: ## Introduction This module is designed to help participants understand the basics of data preprocessing, which is an essential part of any machine learning project. Data preprocessing is the process of transforming raw data into a format that can be used by machine learning algorithms. It is a critical step in the machine learning pipeline, and it is often overlooked by practitioners. ## Learning Outcomes - Understand the basics of data preprocessing - Understand the importance of data preprocessing - Understand the steps of data preprocessing - Understand the advantages of data preprocessing - Understand the disadvantages of data preprocessing - Understand the common machine learning algorithms ## Topics - What is data preprocessing? - Why is data preprocessing important? - Steps of data preprocessing - Advantages of data preprocessing - Disadvantages of data preprocessing - Common machine learning algorithms ## Introduction This module is designed to help participants understand the basics of data preprocessing, which is an essential part of any machine learning project. Data preprocessing is the process of transforming raw data into a format that can be used by machine learning algorithms. It is a critical step in the machine learning pipeline, and it is often overlooked by practitioners. ## Learning Outcomes - Understand the basics of data preprocessing - Understand the importance of data/process/preprocessing - Understand the steps of data preprocessing - Understand the advantages of data preprocessing - Understand the disadvantages of data preprocessing - Understand the common machine learning algorithms ## Topics - What is data preprocessing? - Why is data preprocessing important? - Steps of data preprocessing - Advantages of data preprocessing - Disadvantages of data preprocessing - Common machine learning algorithms ## What is data preprocessing? Data preprocessing is the process of transforming raw data into a format that can be used by machine learning algorithms. It is a critical step in the machine learning pipeline, and it is often overlooked by practitioners. ## Why is data preprocessing important? Data preprocessing is important because it prepares the data for machine learning algorithms. It is a critical step in the machine learning pipeline, and it is often overlooked by practitioners. ## Steps of data preprocessing - Data cleaning - Data normalization - Data encoding - Data splitting - Data augmentation - Data visualization ## Advantages of data preprocessing - Improves the accuracy of machine learning algorithms - Improves the performance of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - Improses the interpretability of machine learning algorithms - Improves the interpretability of machine learning algorithms - 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46 minit10 tontonan

Unduh Subtitle SNSDE-011