1. Fork this repository
2. Create a folder with your Team Name
3. Upload all the code and necessary files in the created folder
4. Upload a README.md file in your folder with the below mentioned informations.
5. Generate a Pull Request with your Team Name. (Example: submission-XYZ_team)

The developed prototype of SurakshaNivesh offers a tangible glimpse into the platform's envisioned functionalities and user experience. It is a dynamic visualization of the innovative solutions that SurakshaNivesh brings to the realm of investment. The frontend is built in React with the backend and AI algos in python.

Through the prototype, users can interact with a simulated version of the platform's interface, exploring key features such as influencer credibility analysis, real-time sentiment monitoring, personalized recommendations, and collaboration with regulatory authorities. Each feature is showcased in an intuitive manner, allowing users to understand how they function and contribute to safeguarding investments.

The prototype's interface mirrors the actual user journey, from navigating the dashboard to accessing educational resources and receiving real-time alerts. It encapsulates the seamless integration of advanced technologies, including machine learning algorithms, real-time data analysis, and sentiment analysis, all orchestrated to provide users with accurate information and proactive protection.

Frontend: React (Frontend framework) Redux (State management) HTML, CSS, JavaScript (Frontend markup and styling) Axios (HTTP requests) Material-UI or other UI libraries (User interface components) React Router (Navigation)

Backend: Node.js (Backend runtime environment) Express.js (Backend framework) MongoDB or MySQL (Database management) Mongoose (MongoDB ODM) or Sequelize (MySQL ORM) Passport.js (Authentication) JSON Web Tokens (JWT) (Authentication and authorization) REST API or GraphQL (API communication)

Machine Learning and AI: Python (Machine learning and data processing) scikit-learn, TensorFlow, or PyTorch (Machine learning libraries) Natural Language Processing (NLP) libraries (spaCy, NLTK) Sentiment analysis libraries

Real-time Monitoring: WebSocket (Real-time communication)

Data Analysis and Anomaly Detection: Python (Data analysis and processing) pandas, numpy (Data manipulation and analysis) Machine learning libraries for anomaly detection (scikit-learn, Isolation Forest)

Collaboration with Regulatory Authorities: APIs for regulatory authorities' systems

Testing and Deployment: Jest, React Testing Library (Frontend testing) Mocha, Chai (Backend testing) Continuous Integration and Deployment tools (e.g., Jenkins, Travis CI) Docker (Containerization) Nginx or Apache (Web server) Cloud platforms for deployment (e.g., AWS, Heroku)

Version Control and Collaboration: Git (Version control) GitHub, GitLab, Bitbucket (Code hosting and collaboration)

Others: Postman (API testing) VS Code or preferred code editor Command-line tools for development and deployment

The prototype is built on React.js, All the files are in this repo. But to make it easier for demonstration, I have hosted it on Figma's Prototype server too, so you can take a look by clicking through the following link: https://bit.ly/surakshanivesh or https://www.figma.com/proto/pw7ZcD3tLDpszEpGGSe3wH/SurakashNivesh?page-id=0%3A1&type=design&node-id=3-1297&viewport=1020%2C175%2C0.16&t=uZWIy4pEp209U437-1&scaling=min-zoom&starting-point-node-id=3%3A1297&mode=design

The app is just in prototype phase as of now, and contains dummy data for now.

Embarking on the development journey of the SurakshaNivesh prototype as a solo endeavor was a remarkable learning experience that brought forth profound insights into the realm of technology implementation. Among the pivotal takeaways was the seamless integration of diverse AI algorithms, which demanded an in-depth grasp of orchestrating intricate machine learning models, real-time data analysis, and sentiment analysis techniques. This journey underscored the transformative potential of harnessing advanced AI technologies to fashion a cohesive platform that empowers investors with informed decision-making capabilities. Additionally, crafting a user-centric design unveiled the significance of creating intuitive interfaces that resonate with users and harmonize seamlessly with the complexity of advanced functionalities. While steering through the development process, the multifaceted nature of the project demanded hands-on engagement across disciplines, spanning the roles of a UI/UX designer, backend and frontend developer, data scientist, and even regulatory compliance expert. Furthermore, this autonomous expedition granted a firsthand understanding of aligning AI-driven features with stringent regulatory norms, shedding light on the intricate compliance landscape. Ultimately, the process of conceptualizing and crafting the SurakshaNivesh prototype proved instrumental in enhancing technical acumen while unearthing the immense potential that AI algorithms hold in shaping innovative financial technology solutions.