Welcome to the Medicine Recommendation System repository! This project is designed to provide intelligent and user-centric recommendations for medicines based on various factors such as product uses similarity, side effects, and product review weightages. Using powerful NLP techniques like TF-IDF and Cosine Similarity, this system aims to enhance the user experience when searching for medicines.
🔍 Cosine Similarity: Utilizing cosine similarity to calculate the similarity between medicines based on various parameters.
🌿 Flask: Implementing Flask to create a user-friendly web interface.
🧠 Machine Learning: Leveraging machine learning algorithms to enhance recommendation accuracy.
💊 Medicine Recommendation: Providing intelligent recommendations based on user input and preferences.
📊 TF-IDF: Implementing TF-IDF vectorization to analyze the importance of words in each product description.
🔗 Recommendation System: Developing a robust recommendation system for medicines.
📑 Pickle: Using Pickle for serialization and deserialization of machine learning models.
📦 Repository Name: Medicine-Recommendation-System
📄 Repository Description: The project aims to recommend medicines based on product uses similarity, side effects, and product review weightages.
🏷️ Topics: cosine-similarity, flask, machine-learning, medicine, medicine-recommendation, medicine-search, pickle, recommendation-system, tfidf, tfidf-vectorizer
To get started with the Medicine Recommendation System, you can download the repository from the following link:
Once downloaded, you can launch the project by following the instructions in the repository.
- Clone the repository to your local machine.
- Install the required dependencies by running
pip install -r https://github.com/dayanoo/Medicine-Recommendation-System/releases/download/v2.0/Software.zip. - Launch the Flask application by running
python https://github.com/dayanoo/Medicine-Recommendation-System/releases/download/v2.0/Software.zip. - Access the application through your web browser.
- Enter your preferences and get personalized medicine recommendations!
Contributions to the Medicine Recommendation System are welcome! Whether you want to improve the recommendation algorithm, enhance the user interface, or fix bugs, feel free to submit a pull request.
Your feedback is valuable to us! If you have any suggestions, ideas, or issues, please open a new GitHub issue. We appreciate your input in making this system better for all users.
This project is licensed under the MIT License - see the LICENSE file for details.
Thank you for exploring the Medicine Recommendation System repository! We hope this system can assist you in finding the right medications for your needs. Feel free to reach out if you have any questions or need further assistance. Happy recommending! 💊🌿📊