From 1d776aea5b6881a921c632586d8bc985dd7b29b9 Mon Sep 17 00:00:00 2001 From: Evaclaire Wamitu Date: Tue, 30 Jul 2024 20:28:41 +0300 Subject: [PATCH] Add deployment section --- movie_recommendor.ipynb | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/movie_recommendor.ipynb b/movie_recommendor.ipynb index ff7e36c..752b0b8 100644 --- a/movie_recommendor.ipynb +++ b/movie_recommendor.ipynb @@ -2692,7 +2692,8 @@ " best_model_params = knn_best_params\n", " best_model_name = 'KNN'\n", " best_score = knn_best_score\n", - " \n", + " \n", + " # Print the best model and best RMSE score\n", " print(f\"\\nBest model: {best_model_name}\")\n", " print(f\"\\nBest RMSE: {best_score}\")\n", " \n", @@ -3676,6 +3677,22 @@ "plot_rmse_vs_weight(weights, rmse_scores)\n" ] }, + { + "cell_type": "markdown", + "id": "53328243-2794-41fc-aff0-0899b13c0652", + "metadata": {}, + "source": [ + "## Deployment on Streamlit" + ] + }, + { + "cell_type": "markdown", + "id": "1c0548a9-2cec-43b9-9cb1-03523fa09506", + "metadata": {}, + "source": [ + "Streamlit is a Python library that simplifies the creation of web applications for data science and machine learning projects. In this deployment, Streamlit is used to create an interactive movie recommendation system. The app features the collaborative filtering model using the SVD algorithm which was trained on user-movie ratings data. The model was chosen due to its better accuracy score as continuous improvement is performed on the hybrid model. \n" + ] + }, { "cell_type": "markdown", "id": "986c0d7d-209c-4860-83fa-cec0add9783d",