Sai Durga Prasad's repositories
Remove-Background-from-the-Image
Creating a user-friendly solution for image background removal using the U2-Net model. Enhancing accuracy and processing speed to aid graphic design, e-commerce, and photography tasks.
Book-Recommendation-System
A concise guide exploring techniques for building accurate and engaging book recommendation systems, catering to diverse reader preferences.
ChatBot
Creating a versatile, AI-powered ChatBot using ChatGPT for engaging and efficient customer interactions. Prioritizing real-time responses, personalization, and seamless integration with existing systems. Enhancing customer satisfaction through timely and accurate query handling.
Customer-churn-prediction
Developing a customer churn prediction model using machine learning techniques. The model identifies potential churners by analyzing historical customer data, aiding businesses in retaining customers and boosting satisfaction. Evaluation based on accuracy, precision, recall, and F1 score. Emphasis on data quality and relevant features.
Image-Classification
Developed an image classification web app using CNN to differentiate cats and dogs. Achieved high accuracy, precision, recall, and F1 score. Pipeline involves data preprocessing, model training, Docker deployment on AWS ECS, user-friendly interface, and reliable CI/CD. Showcases deep learning's potential in image analysis.
PolyInnovate
Poly AI Research bot is a user-friendly news research tool designed for effortless information retrieval.
pytorch-lightning
Deep learning framework to train, finetune and deploy AI models
remote-jobs
A list of semi to fully remote-friendly companies (jobs) in tech.
Text-summarization-project
Automating text summarization using machine learning techniques. Utilizing the Samsum dataset, our model generates concise summaries while retaining key information. Improves content comprehension and efficiency for information retrieval, content curation, and productivity enhancement.
HR_analysis
Creating a model to predict employee retention, aiding HR in risk identification and retention strategies. Emphasizing accuracy, precision, recall, and F1 score. Encompasses data collection, preprocessing, feature engineering, model training, and evaluation stages.
OLS-Regression
Predict cancer mortality rates for US counties. Using Regression algorithms
Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
US-House-Analysis
The primary goal is to build a regression model that accurately predicts house prices in the US based on various features, such as location, square footage, number of bedrooms, and more.