Encoding
Encoding is the process of converting data from one format to another for efficient transmission or storage. In data science and artificial intelligence, encoding is used to transform categorical data into numerical data that can be used in machine learning models. This is important because most machine learning algorithms cannot process categorical data directly. Encoding techniques include one-hot encoding, label encoding, and binary encoding. One-hot encoding creates a binary vector for each category, where only one element is 1 and the rest are 0s. Label encoding assigns a unique numerical value to each category. Binary encoding converts each category into a binary code. Encoding is a crucial step in data preprocessing for machine learning and can greatly impact the accuracy of the model.
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