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18 changes: 14 additions & 4 deletions learn.json
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Original file line number Diff line number Diff line change
@@ -1,15 +1,25 @@
{
"slug" : "random-forest-project-tutorial",
"title" : "Random Forest Project Tutorial",
"title" : {
"us": "Random Forest Project Tutorial",
"es": "Tutorial del proyecto Bosque Aleatorio"
},
"preview": "https://github.com/4GeeksAcademy/random-forest-project-tutorial/blob/main/preview.png?raw=true",
"solution": "https://github.com/4GeeksAcademy/random-forest-project-tutorial/blob/main/solution.ipynb",
"status": "published",
"translations": ["us"],
"technologies": ["data-science", "machine-learning"],
"technologies": ["python", "pandas", "numpy", "matplotlib", "scikit-learn", "data-science", "machine-learning"],
"difficulty": "beginner",
"syntax": "python",
"duration" : 2,
"template_url": "https://github.com/4GeeksAcademy/machine-learning-python-template",
"projectType": "project",
"description" : "Use Random Forest algorithm to predict a marketing campaign success by predicting the campaign impressions",
"gitpod": true
"autoPlay": "false",
"description" : {
"us": "In this project, you'll enhance the prediction accuracy of a decision tree model by implementing a random forest. Using a dataset from a previous project, you'll build, train, and analyze a random forest, modifying hyperparameters to improve accuracy. Finally, you'll save and document the model.",
"es": "¡En este proyecto, mejorarás la precisión de predicción de un modelo de árbol de decisión implementando un bosque aleatorio. Usando un conjunto de datos de un proyecto anterior, construirás, entrenarás y analizarás un bosque aleatorio, modificando los hiperparámetros para mejorar la precisión. Finalmente, guardarás y documentarás el modelo."
},
"telemetry": {
"batch": "https://breathecode.herokuapp.com/v1/assignment/me/telemetry?asset_id=425"
}
}