The case study focuses on the most popular technique of Supervised Machine Learning algorithm, SVM its basics of Support Vector Machines (SVM) and how it can be used to Predict drug type.
This case provides a deep understanding on how to build a support vector machine model to suitably categorize the drug based on the condition of the person.
The case helps the learner to implement data visualization techniques to understand several hidden patterns and analyze the relationship that exists between variables.
Working understanding of feature engineering techniques such as one hot encoding to convert categorical data to numerical data, as most algorithms do not support categorical input.
The case helps the learner to train and apply support vector machine model, to predict the class of drug effectively for future scenarios.
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Difficulty: Advanced
Duration: Approximately 3 hours
