Create README.md

README.md

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+---
+language:
+- en
+metrics:
+- accuracy
+tags:
+- sklearn
+- machine learning
+- movie-genre-prediction
+- multi-class classification
+---
+
+## Model Details
+
+### Model Description
+
+The goal of the competition is to design a predictive model that accurately classifies movies into their respective genres based on their titles and synopses.
+
+The model takes in inputs such as movie_name and synopsis as a whole string and outputs the predicted genre of the movie.
+
+
+
+- **Developed by:** [Shalaka Thorat]
+- **Shared by:** [Data Driven Science- Movie Genre Prediction Contest: competitions/movie-genre-prediction]
+- **Language:** [Python]
+- **Tags:** [Python, NLP, Sklearn, NLTK, Machine Learning, Multi-class Classification, Supervised Learning]
+
+### Model Sources
+
+- **Repository:** [competitions/movie-genre-prediction]
+
+## Training Details
+
+We have used Multinomial Naive Bayes Algorithm to work well with Sparse Vectorized data, which consists of movie_name and synopsis.
+The output of the model is a class (out of 10 classes) of the genre.
+
+### Training Data
+
+All the Training and Test Data can be found here:
+
+[competitions/movie-genre-prediction]
+
+#### Preprocessing
+
+1) Label Encoding
+2) Tokenization
+3) TF-IDF Vectorization
+4) Preprocessing of digits, special characters, symbols, extra spaces and stop words from textual data
+
+## Evaluation
+
+The evaluation metric used is [Accuracy] as specified in the competition.
+