| title | emoji | colorFrom | colorTo | sdk | sdk_version | app_file | pinned |
|---|---|---|---|---|---|---|---|
FilmFlix |
📈 |
gray |
red |
streamlit |
1.9.0 |
app.py |
false |
Link to the app: https://filmflix-0.herokuapp.com/
It contains posters of Top 6 most liked and most popular movies.These movies are sorted based on number of like and popularity measures.
This works based on content based recommender system using cosine similarity.Cosine similarity is a metric used to measure how similar two items are.
This section first performs exploratory data analysis on the dataset and some useful plots are displayed.
Then it builds three ml models:
-
KNearestNeigbour
-
GradientBoostingClassifier
-
LogisticRegression
Then it compares the accuracy of three models and suggests genre of the movie based on high accuracy.
This section searches and filters the five genres of the movie.
- Action
- Romance
- Thriller
- Comedy
- Drama
This section recommends music based on language, mood and favourite singer of the user.
1.Python
2.Streamlit
3.TMDb api
4.Html (inside streamlit.components.v1)
1.Clone or download this repository to your local machine.
2.Then install the virtal environment in the file directory using the command:
python -m venv my_venv.
3.Activate the virtual environment by the placing the relative path of Activate.ps1 in my_venv:
my_venv\Scripts\Activate.ps1
4.pip install -r requirements.txt
5.streamlit run app.py
