Update README.md

README.md

@@ -9,6 +9,30 @@ app_file: app.py
 license: apache-2.0
 ---
 
-#### Hugging Face Space Link : [Click Me](https://huggingface.co/spaces/akshatsanghvi/movie-recommender-system)
-#### Kaggle Dataset (Bollywood) : [Click Me](https://www.kaggle.com/datasets/pncnmnp/the-indian-movie-database)
-#### Kaggle Dataset (Hollywood) : [Click Me](https://www.kaggle.com/datasets/neha1703/movie-genre-from-its-poster?select=MovieGenre.csv)
+## Movie Recommender System
+A movie recommendation system, or a movie recommender system, is an ML-based approach to filter or predict the users’ film preferences using techinques like :
+- popularity-based
+- content-based
+- collabrative filtering
+
+
+In this, project I have used content-based filtering to fiter movies with similar tags (concatenated strings of story, gernre, and title column)
+
+## Links :
+
+- #### Hugging Face Space Link : [Click Me](https://huggingface.co/spaces/akshatsanghvi/movie-recommender-system)
+- #### Kaggle Dataset (Bollywood) : [Click Me](https://www.kaggle.com/datasets/pncnmnp/the-indian-movie-database)
+- #### Kaggle Dataset (Hollywood) : [Click Me](https://www.kaggle.com/datasets/neha1703/movie-genre-from-its-poster?select=MovieGenre.csv)
+
+## After you click on the HF link you'll see two buttons,
+#### "Recommend" Button : Recommends 5 similar movies from the same country as of movie.
+#### "🌍" Button : Recommends 10 similar movies from the world.
+
+## Step 1:
+![ss1](https://user-images.githubusercontent.com/92530735/220027045-6a009d71-d524-4a20-8a38-6ec7a813fd17.png)
+
+## Step 2:
+![ss2](https://user-images.githubusercontent.com/92530735/220027275-d85b1336-2a14-4336-8383-62c0c7e8a6d0.png)
+
+## Step 3:
+![ss3](https://user-images.githubusercontent.com/92530735/220027380-b711ece2-eb2e-44d2-8abc-b83cc116ba9a.png)