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@article{166746,
        author = {Shishira Pillamarapu and Dr Bhargavi Peddireddy and Shirisha Gujja},
        title = {Investment Recommendation System using Machine Learning and Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {2598-2602},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166746},
        abstract = {Creating a personalized investment plan is crucial for anyone who wants to achieve their financial goals. Whenever a personalized plan is created, it is tailored to the people's needs and based on risk tolerance and investment goals. Without a customized plan, it is too easy to make haphazard investment decisions that do not align with overall financial objectives, leading to unnecessary risks and suboptimal returns. For a common man, investment options like Stock Market, Mutual Funds, etc. seem a very complicated and confusing task. A common man is very cautious of the money that he/she is investing on anything. The paper introduces a simplified Investment Recommendation System designed to provide basic investment guidance to users based on their risk preference, age, income, and occupation, with the help of Artificial Intelligence and Machine Learning techniques to enhance the decision- making process for investors. The primary aim is to assist users in making investment decisions aligned with their financial circumstances and risk tolerance. It gives stock investment recommendations, mutual funds investment recommendations, gold investment recommendations, and real estate investment recommendations.},
        keywords = {LSTM Network, Random Forest Regressor, Gradient boosting regressor},
        month = {July},
        }