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Commit0d370f6

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GITBOOK-81: Image Resizing - Machine Learning
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‎docs/machine-learning/1.-data-sets.md‎

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#1. Data Sets
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1. Click on_**Data Sets**_ in the_**Machine Learning**_ category.
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‎docs/machine-learning/10.-fit-predict.md‎

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#10. Fit/Predict
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1. Click on_**Fit/Predict**_ under the_**Machine Learning**_ category.
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‎docs/machine-learning/11.-model-info.md‎

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#11. Model Info
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1. Click on_**Model Info**_ in the_**Machine Learning**_ category.
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‎docs/machine-learning/12.-evaluation.md‎

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#12. Evaluation
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1. Click on_**Evaluation**_ in the_**Machine Learning**_ category.
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###Regression / Classification
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1._**Target Data**_: Specify the target data.
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2._**Predict Data**_: Specify the data to predict.
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###Clustering
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1._**Clustered Index**_: Load the data containing index information assigned to the original data by clusters.
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2._**Feature Data**_: Load the original data. The_**Silhouette Score**_ is derived through computations with the data specified in the_**Clustered Index**_.

‎docs/machine-learning/14.-save-load.md‎

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#14. Save / Load
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1. Click on_**Save/Load**_ in the_**Machine Learning**_ category.
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‎docs/machine-learning/2.-data-split.md‎

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#2. Data Split
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1. Click on_**Data Split**_ in the_**Machine Learning**_ category.
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‎docs/machine-learning/3.-data-prep.md‎

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#3. Data Prep
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1. Click on**Data Prep** in the**Machine Learning** category.
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‎docs/machine-learning/4.-automl.md‎

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#4. AutoML
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1. Click on_**AutoML**_ in the_**Machine Learning**_ category.
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‎docs/machine-learning/5.-regressor.md‎

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#5. Regressor
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1. Click on the_**Regressor**_ in the_**Machine Learning**_ category.
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###ElasticNet
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1._**Alpha**_: Adjust the level of regularization.
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2._**L1 ratio**_: Adjusts the balance (ratio) between_**L1 (Lasso)**_ and_**L2 (Ridge)**_ regularization.
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###XGB Regressor
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1._**N estimators**_: Specifies the number of trees in the ensemble.
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2._**Max depth**_: Specifies the maximum depth of the tree.

‎docs/machine-learning/6.-classifier.md‎

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#6. Classifier
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1. Click on the_**Classifier**_ under the_**Machine Learning**_ category.
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###SupportVectorMachine Classifier
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1._**C**_: C indicates the freedom of the model's regularization. A higher C value makes the model more complex to fit the training data.
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2._**Kernel**_: A function that maps data into higher dimensions. You can control the complexity of the model by selecting the kernel type.

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