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ML.NET : CODE EXECUTION PATH

  🎨 Visual Journey The Student's Path Through the System ┌────────────┐ │ INPUT │ │ Request │ │ ┌────────┐ │ │ │ 95 │ │ │ │ 90 │ │ │ │ 92 │ │ │ └────────┘ │ └────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────────────┐ │ STUDENT OBJECT CREATION │ │ │ │ ┌────────────────────────────────────────────────────────┐ │ │ │ StudentData │ │ │ │ ┌──────────────────────────────────────────────────┐ │ │ │ │ │ Attendance: 95 │ │ │ │ │ │ InternalMarks: 90 │ │ │ │ │ │ AssignmentMarks: 92 │ │ │ │ │ │ Result: null (to be predicted) │ │ │ │ │ └──────────────────────────────────────────────────┘ │ │ │ └───────────...
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Core MACHINE LEARNING - ML.NET

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  Core MACHINE LEARNING - ML.NET  SALARY PREDICTION WEBAPI Part 1: Project Overview ❓ What are we building? We're building a Salary Prediction Web API that uses Machine Learning ( ML.NET ) to predict an employee's salary based on their years of experience . The model learns from historical data (experience vs. salary) and then predicts salaries for new inputs. 🤔 Why are we building this? Real-world application : HR departments and job seekers use similar models for salary estimation Regression problem : This is a classic example of predicting a continuous value (salary) Learn ML basics : Introduces regression algorithms, data pipelines, and prediction engines 🛠️ How: Key ML Concepts Concept What It Means Why It Matters Features Input data (Years of Experience) What the model uses to make predictions Label Output/target value (Salary) What the model learns to predict Training Data Historical data with known salaries The "textbook" the model studies Regression Predi...
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