SHRUTI MAURYA

Aspiring Machine Learning Engineer

285-B, New MIG flats Mayur Vihar Phase 3, Delhi-110096, 110096, Delhi, IN.

About

A highly motivated and results-driven B.Tech student in Computer Science (AI & ML) with a strong foundation in developing and deploying predictive models and recommendation systems. Demonstrated expertise in Python, TensorFlow, Scikit-learn, and data preprocessing, evidenced by projects achieving up to 92% accuracy and 60% reduction in processing time. Eager to leverage advanced machine learning skills and a passion for innovation to contribute to dynamic technical teams in the AI/ML industry.

Volunteer

ML Club Core Member

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VIT Bhopal University

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Actively contributed to the ML Club, leading hackathon teams and expanding expertise in diverse technical domains relevant to machine learning and quantitative modeling.

Highlights

Led a team in the MariaDB Python Hackathon, successfully developing database-driven ML solutions for over 100 participants.

Completed "Finance 101" by StockPe, gaining foundational expertise in algorithmic trading and quantitative modeling principles.

Education

VIT Bhopal University

Bhopal, Madhya Pradesh, India
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B.Tech Computer Science (AI & ML) Grade: 7.68/10.0 CGPA

Languages

English

Hindi

Certificates

Oracle OCI AI Foundations

Oracle

AWS Certified Solutions Architect - Associate

Amazon Web Services

IBM SkillsBuild Gen AI

IBM

Skills

Programming Languages

Python, SQL, Java, C++.

Machine Learning

TensorFlow, Scikit-learn, LSTM, Neural Networks, Predictive Modeling.

Databases

MySQL, PostgreSQL, Data Warehousing.

Development Tools

Jupyter Notebooks, Git, Gradio, Streamlit, Microsoft Excel.

Data Preprocessing

MinMaxScaler, Sliding Windows, Feature Engineering, TF-IDF Vectorization.

Model Deployment

Hugging Face, Gradio, Streamlit.

Data Analysis

Pandas.

Quantitative Modeling

Algorithmic Trading, Financial Analysis.

Projects

Stock Price Prediction using LSTM

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Summary

Led the development and deployment of an LSTM-based stock price prediction model, significantly enhancing accuracy and reducing data processing time.

Diabetes Prediction System

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Summary

Designed and deployed a machine learning-driven diabetes prediction system, achieving high accuracy and providing real-time diagnostic support for healthcare professionals.

Content-Based Movie Recommender

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Summary

Constructed a content-based movie recommendation engine capable of processing a large dataset and delivering highly relevant, personalized suggestions efficiently.