Classification Example in Machine Learning | Patient Dataset Explained | Kapil Joshi Tutorials

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In this video, we explain a simple yet very important classification example widely used in Machine Learning, Data Mining, and Artificial Intelligence.
We take a patient dataset where each record includes:
• Gender (Male/Female)
• Age
• Health Status (Healthy or Sick)
Using this example, you will clearly understand:
• What is Supervised Learning
• What is Binary Classification
• How input features and target labels work
• How machine learning models learn patterns from data
• How predictions are made for new unseen data
This example is commonly used to explain algorithms such as:
• Decision Trees
• Naive Bayes Classifier
• k-Nearest Neighbors (KNN)
• Logistic Regression
The video is ideal for:
• B.Tech / M.Tech students
• Beginners in Machine Learning
• Exam preparation (GATE, NET, university exams)
• Anyone starting with AI & Data Science
📌 Topics Covered:
• Labeled dataset
• Input features vs output labels
• Supervised learning
• Binary classification
• Real-world medical applications
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Faculty of Computer Science & Engineering (CSE)


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