added folder google-colab

Google-colab-methods/metodo_4_aprueba.ipynb

@@ -0,0 +1,75 @@
+{
+ "nbformat": 4,
+ "nbformat_minor": 0,
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "name": "python3",
+ "display_name": "Python 3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "czzTKWpsdadd",
+ "outputId": "cfa697a8-e18c-4914-a0d3-19e8af0d6929"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Enter a review for classification: nice video\n",
+ "1/1 [==============================] - 0s 58ms/step\n",
+ "Prediction: 0.6315826177597046\n",
+ "Positive review!\n"
+ ]
+ }
+ ],
+ "source": [
+ "from tensorflow.keras.models import load_model\n",
+ "from tensorflow.keras.datasets import imdb\n",
+ "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
+ "\n",
+ "\n",
+ "\n",
+ "# Cargar el modelo guardado\n",
+ "model = load_model('modelo.h5')\n",
+ "\n",
+ "# Prompt the user to enter a review for classification\n",
+ "user_review = input(\"Enter a review for classification: \")\n",
+ "# the movie was very stupid and bad the worsdt movie in al times :negative\n",
+ "# nice video : positive\n",
+ "\n",
+ "# Tokenize the user's review using the IMDB dataset's word index\n",
+ "word_index = imdb.get_word_index()\n",
+ "user_tokens = [word_index[word] if word in word_index else 0 for word in user_review.split()]\n",
+ "\n",
+ "# Pad the user's tokens to a maximum length of 256 words\n",
+ "maxlen = 256\n",
+ "user_padded = pad_sequences([user_tokens], maxlen=maxlen)\n",
+ "\n",
+ "# Use the trained model to predict the sentiment of the user's review\n",
+ "prediction = model.predict(user_padded)[0][0]\n",
+ "\n",
+ "# Print the predicted sentiment\n",
+ "if prediction >= 0.5:\n",
+ " print(f\"Prediction: {prediction}\")\n",
+ " print(\"Positive review!\")\n",
+ "else:\n",
+ " print(f\"Prediction: {prediction}\")\n",
+ " print(\"Negative review.\")"
+ ]
+ }
+ ]
+}