<<<<<<< HEAD # Python_AI_Projekt Projekt för Pythonkurs (AI) Autoencoders Scikit-learn: - K-nearest neighbors ======= # 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 >>>>>>> b992895c329b4c147193b68b17c8181bb17fb220