Welcome to the Ted-Talk-Recommendation-System! This project utilizes NLP techniques and cosine similarity to recommend Ted Talks based on user preferences.
- The recommendation system employs TF-IDF (Term Frequency-Inverse Document Frequency) technique for converting text to vectors.
- Cosine similarity is used to measure the similarity between vectors and recommend relevant Ted Talks.
- Flask has been chosen for the deployment of this recommendation system.
- Make sure you have Flask and nltk libraries installed to run this project.
- Clone the project repository.
- Extract the project files.
- Locate the cs.zip file within the extracted files. This archive contains the necessary .pkl file used in deployment.
- Extract the contents of cs.zip.
- Ensure that the extracted
cs.pklfile is in the same folder as the project.
- Execute the necessary commands to run the project, and you're ready to explore and enjoy personalized Ted Talk recommendations!
Feel free to reach out if you have any questions or encounter issues. Happy recommending!