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# Python_AI_Projekt
Projekt för Pythonkurs (AI)


Autoencoders
Scikit-learn: - K-nearest neighbors
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# 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 


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