This project automates the analysis of large-scale customer feedback using Natural Language Processing (NLP) and Machine Learning. The core of this tool is a model that instantly translates raw review text into a corresponding star rating, providing rapid and actionable insights into product satisfaction.
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Links: GitHub Repository
Jivafit is a deep learning project that uses a Multi-Layer Perceptron (MLP) to analyze various health-related data points and predict disease risk. The model is designed to provide actionable insights into potential health risks, offering a scalable and predictive tool for public health analysis.
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Links: GitHub Repository
This data science project analyzes historical transaction and customer behavior data to build a predictive model for forecasting revenue and optimizing marketing strategies. The core of this tool is a Random Forest regression model, which combines multiple decision trees to provide robust predictions of a customer's total purchase value. The model also provides insights into which factors most influence a customer's spending, allowing for more informed business decisions.
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Links: GitHub Repository
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🔭 I’m currently developing a project called Jiva Fit, where I'm applying a Multi-Layer Perceptron to predict disease risk.
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🌱 I’m currently learning Deep Learning and Power BI.
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👨💻 All of my projects are available at https://datascienceportfol.io/ayushkumar1891
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💬 Ask me about Python, SQL, and Pandas.
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📫 How to reach me: [email protected]
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📄 You can download my resume here: Ayush_Kumar_Resume.pdf
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⚡ Fun fact: I enjoy playing basketball and doing calisthenics.
Thank you for taking the time to review my profile and projects. I'm always open to feedback and collaboration!