From 01760493622a584314ec7ae83ef8c21ed3eb0923 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jimmy=20Wr=C3=A5dhe?=
 <38496210+jwradhe@users.noreply.github.com>
Date: Sat, 26 Oct 2024 19:36:27 +0200
Subject: [PATCH 1/2] Update README.md

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-# Python_AI_Projekt
-Projekt för Pythonkurs (AI)
+# Supervised Learning - Movie/TVShow recommender
+

From b992895c329b4c147193b68b17c8181bb17fb220 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jimmy=20Wr=C3=A5dhe?=
 <38496210+jwradhe@users.noreply.github.com>
Date: Sat, 26 Oct 2024 19:59:38 +0200
Subject: [PATCH 2/2] Update README.md

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 1 file changed, 52 insertions(+), 1 deletion(-)

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-# Supervised Learning - Movie/TVShow recommender
+# Supervised Learning - Movie/TV-Show recommender
+
+## Specification
+Movie/TV-Show recommender
+
+This program will recommend you what movie or th-show to view based on what Movie/TV-Show you like.
+
+### Data Source:
+I will use 4 datasets from kaggle, 3 datasets from streaming-sites Netflix, Amazon Prime and Disney Plus, also 1 from a IMDB dataset.
+
+### Model:
+I will use k-Nearest Neighbors (k-NN) alhorithm that can help me find other titles based on features like Title, Release year, Description, Cast, Director and genres.
+
+### Features:
+1.  Load data and preprocessing before creating new dataset csv file.
+2.  Model training with k-NN algorithm.
+3.  
+
+### Requirements:
+1. Title data:
+  * Title
+  * Genres
+  * Release year
+  * Cast
+  * Director
+  * Description
+2. User data:
+  * What Movie / TV-Show
+  * What genre
+  * Director
+
+### Libraries
+  * pandas: Data manipulation and analysis
+  * scikit-learn: machine learning algorithms and preprocessing
+  * numpy: numerical operations
+  * beatifulsoup4: web scraping
+    
+### Classes
+  1. LoadData
+     * Loading, cleaning and saving alla data to csv
+     * check_data
+     * clean_text
+     * clean_data
+     * load_dataset
+     * create_data
+     * save_data
+     * load_data
+  2. UserData
+     * input
+  3. Recommendations
+     * get_recommendations 
+