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| """ | |
| Análisis de Reseñas de Transporte en Santiago | |
| Evaluación 2 - Machine Learning | |
| """ | |
| import pandas as pd | |
| import numpy as np | |
| from sklearn.model_selection import train_test_split, KFold | |
| import warnings | |
| warnings.filterwarnings('ignore') |
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| import os | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import tensorflow as tf | |
| from tensorflow.keras.preprocessing import image | |
| from tensorflow.keras.applications.mobilenet_v2 import MobileNetV2, preprocess_input, decode_predictions | |
| # ----------------------------- | |
| # CONFIGURACIONES | |
| # ----------------------------- |
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| import mysql.connector | |
| import anthropic | |
| from datetime import datetime | |
| import json | |
| # Configuración de la conexión a MySQL | |
| db_config = { | |
| 'host': 'localhost', | |
| 'user': '----', | |
| 'password': '-----', |
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| # IMPLEMENTACIÓN DE MODELOS PREDICTIVOS. CASO PREDICTIVO DE MERMAS | |
| import pandas as pd | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.preprocessing import StandardScaler, OneHotEncoder | |
| from sklearn.compose import ColumnTransformer | |
| from sklearn.pipeline import Pipeline |
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| #install.packages("RMySQL") | |
| #install.packages("dplyr") | |
| #install.packages("ggplot2") | |
| #2.- Habilitacion de paquetes | |
| library(RMySQL) | |
| library(dplyr) | |
| library(ggplot2) | |