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Abhishek Chandragiri's Projects

agile-mlops-deployment-docker-aws-ci-cd-pipeline icon agile-mlops-deployment-docker-aws-ci-cd-pipeline

An end-to-end predictive maintenance application using machine learning to enhance industrial efficiency. This project employs robust modular architecture and advanced MLOps practices, including Docker and AWS for scalable, real-time maintenance predictions.

ai-nlp-based-chatbot-using-dialogflow-for-interactive-portfolio icon ai-nlp-based-chatbot-using-dialogflow-for-interactive-portfolio

"Abhi's Portfolio Assistant" revolutionizes how my professional journey is shared, employing advanced AI and NLP to deliver a dynamic, interactive experience. This Dialogflow-powered chatbot provides an intuitive interface that answers questions about my qualifications and adapts with every interaction.

bmi-prediction-with-mlflow-dagshub icon bmi-prediction-with-mlflow-dagshub

This project applies machine learning models to predict BMI categories based on individual physical attributes, utilizing MLflow for experiment tracking and model management, with integration into DagsHub for collaborative data science workflows. It showcases the power of MLflow in enhancing model lifecycle management and reproducibility.

fine-tuning-llama-2-with-qlora-and-peft icon fine-tuning-llama-2-with-qlora-and-peft

This project enhances the LLaMA-2 model using Quantized Low-Rank Adaptation (QLoRA) and other parameter-efficient fine-tuning techniques to optimize its performance for specific NLP tasks. The improved model is demonstrated through a Streamlit application, showcasing its capabilities in real-time interactive settings.

full-cycle-etl-analytics-with-google-analytics-and-snowflake icon full-cycle-etl-analytics-with-google-analytics-and-snowflake

Explore the transformative power of data analytics in my portfolio, where Google Analytics and Snowflake converge to provide comprehensive insights. This project leverages advanced ETL techniques and real-time data integration to enhance user engagement and optimize content delivery effectively.

machine-learning-based-loan-default-early-warning-system icon machine-learning-based-loan-default-early-warning-system

Developed an end-to-end ML system on Azure to predict loan defaults, leveraging advanced data preprocessing, feature engineering, and machine learning models to optimize accuracy. This project includes a comprehensive suite of tools and techniques for robust financial risk assessment, deployed to enhance decision-making for high-risk exposures.

ml-driven-talent-screening-system icon ml-driven-talent-screening-system

The Advanced Resume Screening App is a powerful tool designed to optimize the hiring process by employing Natural Language Processing (NLP) and Machine Learning (ML).

oil-gas-price-forecasting-model icon oil-gas-price-forecasting-model

The Oil & Gas Price Forecasting Model employs advanced machine learning and time series analysis to accurately predict oil and gas price fluctuations based on historical global reserves data and external market variables.

text-to-chart-ai-transforming-queries-into-visuals icon text-to-chart-ai-transforming-queries-into-visuals

An innovative AI system developed to extract actionable insights by converting natural language into SQL queries via Google's Gemini model and dynamically visualizing the data with Plotly Express, streamlining decision-making across all levels of expertise.

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