classification in machine learning ,20 pages ,mtech cse seminar for advanced machine learning

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This guide covers the essentials of classification and learning objectives, comparing various task types such as binary and multiclass. It delves into algorithms including trees, SVMs, and neural models, emphasizing evaluation metrics and addressing challenges like imbalance and explainability. Additionally, it explores practical applications through case studies in fraud detection and medical diagnosis, while highlighting the importance of responsible deployment and future research...