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2024-11-26 14:13:52 +01:00
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@@ -9,7 +9,7 @@ tags:
- ML
---
# What Is Machine Learning ?
# What Is Machine Learning?
## Introduction
@@ -68,12 +68,9 @@ Once the model type is defined, the next step is to delve into the full workflow
A machine learning project generally follows these steps:
1. **Data Preparation*** Splitting data into training and testing sets.
* Preprocessing: scaling, handling missing values, etc.
2. **Model Training*** Fitting the model on training data: `model.fit(X, y)`.
* Optimising parameters and hyperparameters.
3. **Prediction and Evaluation*** Making predictions on unseen data: `model.predict(X)`.
* Comparing predictions ($$\hat{y}$$) with actual values ($$y$$).
1. **Data Preparation**\* Splitting data into training and testing sets.* Preprocessing: scaling, handling missing values, etc.
2. **Model Training**\* Fitting the model on training data: `model.fit(X, y)`.* Optimising parameters and hyperparameters.
3. **Prediction and Evaluation**\* Making predictions on unseen data: `model.predict(X)`.* Comparing predictions ($$\hat{y}$$) with actual values ($$y$$).
![Modelization in Prog.png](/portfolio/ML/model.png)