Shanthi Priya Ravalapudi

Innovative prompt engineer recognized for high productivity and efficient task completion. Specialized in algorithm development, data analysis, and system optimization to enhance operational workflows. Excel at problem-solving, effective communication, and adaptability, ensuring seamless integration of cutting-edge solutions into existing systems.

• Microsoft Excel Excel from Beginner to Advanced, Udemy
• Data Analyst Training, Udemy
• IIR Recruiter Training Course, Tareeqa Global Solutions PVT. LTD
• HR Generalist & Payroll Training Course, Tareeqa Global Solutions PVT. LTD
• IIR Analytics Training Course, Tareeqa Global Solutions PVT. LTD
• Talent Acquisition Training Course, Tareeqa Global Solutions PVT. LTD
• MS Excel Advanced Training, Tareeqa Global Solutions PVT. LTD
• Interview Cracking Skills Course, Tareeqa Global Solutions PVT. LTD

• Telugu
• English, Fluent
• Telugu, Native

1. Translation Project, Using a statistical Machine Learning Translation technique, IBM model with their Comtrans corpus, using nltk, and can translate from English to French., https://github.com/shantipriya18/MachineLearning/blob/main/Translation_project.ipynb 

2. Text Generation using LSTM & GRU Networks, Developed a neural language model for text generation using Recurrent Neural Networks (LSTM and GRU) to generate human-like text from input sequences. This model was trained with preprocessing steps including tokenization and sequence padding. Both LSTM and GRU architectures were evaluated based on perplexity and output coherence. The final solution was deployed using a Streamlit web app for interactive experimentation., https://github.com/shantipriya18/Machine-Learning/blob/main/textgeneration_using_LSTM_GRU.ipynb 

3. Polynomial Regression Simple Webapp, Developed an interactive web application using Python and Streamlit to demonstrate Polynomial Regression for curve fitting and predictive analysis. This app allows users to upload their own datasets or use synthetic data and dynamically adjust the degree of the polynomial to visualize the effects of underfitting and overfitting in real-time., https://github.com/shantipriya18/Machine-Learning/blob/main/PolynomialRegression_SimpleWebapp%20.ipynb 

4. Multi-Model Q & A using Computer Vision and LLM, Developed a multi-modal question-answering web application that integrates computer vision and a large language model (LLM) to answer user queries based on uploaded images. The system extracts visual features using a vision model and combines them with natural language input to generate context-aware responses., https://github.com/shantipriya18/Machine-Learning/blob/main/MultimodalQA.ipynb 

5. Resume Tracker Using [LLM], Built a Resume Tracker web application using the 1.1.M model 'google/flan-t5-small' to extract and analyze candidate information from resumes. The app parses uploaded resumes, identifies key details like skills, experience, and education, and compares them against job descriptions for relevance.

• Telugu
• English, Fluent
• Telugu, Native