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@@ -9,7 +9,7 @@ tags:
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- ML
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---
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# What Is Machine Learning ?
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# What Is Machine Learning?
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## Introduction
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@@ -68,12 +68,9 @@ Once the model type is defined, the next step is to delve into the full workflow
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A machine learning project generally follows these steps:
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1. **Data Preparation*** Splitting data into training and testing sets.
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* Preprocessing: scaling, handling missing values, etc.
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2. **Model Training*** Fitting the model on training data: `model.fit(X, y)`.
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* Optimising parameters and hyperparameters.
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3. **Prediction and Evaluation*** Making predictions on unseen data: `model.predict(X)`.
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* Comparing predictions ($$\hat{y}$$) with actual values ($$y$$).
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1. **Data Preparation**\* Splitting data into training and testing sets.* Preprocessing: scaling, handling missing values, etc.
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2. **Model Training**\* Fitting the model on training data: `model.fit(X, y)`.* Optimising parameters and hyperparameters.
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3. **Prediction and Evaluation**\* Making predictions on unseen data: `model.predict(X)`.* Comparing predictions ($$\hat{y}$$) with actual values ($$y$$).
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