subhashpolisetti

Automated-ML-with-PyCaret

PyCaret-ML-Workflows is a comprehensive repository showcasing the power and versatility of PyCaret for machine learning tasks. This project includes various workflows for classification, regression, and clustering.

OnboardingBackendSpringboot

OnboardingFrontend

social-media

AutoGluon_ML_End-to-End_Implementations

This repository features practical AutoGluon implementations across tasks like Kaggle competition solutions, tabular classification/regression, multimodal analysis, feature engineering, and multi-label classification. Each Colab notebook runs real-world datasets (text, image, time series) in Google Colab with complete outputs for reproducibility.

blog-microservices-architecture

This project is a microservices-based architecture for a blog platform. It was originally a monolithic application and has been refactored into microservices for better scalability and maintainability. It includes the following microservices:

apache-beam-and-eda-projects

Apache Beam and EDA Projects: Showcasing real-time data processing with Apache Beam, interactive visualizations with D3.js, and automated EDA with Sweetviz and PyCaret. Includes Jupyter notebooks and outputs for learning and exploration.

BizCard_App

Cart-Functionality

cat-dog-classification-cnn

CNN-Based Dogs vs. Cats Image Classifier A Convolutional Neural Network (CNN) model for classifying images of cats and dogs, built using TensorFlow and Keras. This project includes data preprocessing, data augmentation, and transfer learning techniques to achieve high classification accuracy.

subhashpolisetti/timegpt-tabula-rdl-forecasting

subhashpolisetti/CMPE255-Assignment-1

Data Mining Assignment

subhashpolisetti/Decision-Tree-Ensemble-Algorithms

A Python implementation of ensemble learning algorithms from scratch, including Gradient Boosting Machine (GBM), Random Forest, AdaBoost, and Decision Trees. This repository also showcases XGBoost, CatBoost, LightGBM for classification, regression, and ranking tasks, with visualizations and performance comparisons.

subhashpolisetti/Clustering-Techniques-and-Embeddings

This repository includes Colab notebooks demonstrating various clustering algorithms, from scratch-based methods to advanced deep learning models and embeddings. Each notebook features explanations, visualizations, and quality evaluation metrics for clustering performance.

subhashpolisetti/Dimensionality_Reduction

This repository demonstrates various dimensionality reduction techniques on image and tabular datasets. It explores and visualizes methods like PCA, t-SNE, UMAP, ISOMAP, and Autoencoders, comparing their performance and effectiveness with interactive visualizations.

subhashpolisetti/cat-dog-classification-cnn

CNN-Based Dogs vs. Cats Image Classifier A Convolutional Neural Network (CNN) model for classifying images of cats and dogs, built using TensorFlow and Keras. This project includes data preprocessing, data augmentation, and transfer learning techniques to achieve high classification accuracy.

subhashpolisetti/LLM-Threat-model

This project addresses security challenges in implementing a Large Language Model (LLM) system for the Food and Agriculture Organization (FAO). It focuses on securing their document retrieval and analysis platform, which processes sensitive food security and nutrition data.

subhashpolisetti/AutoGluon_ML_End-to-End_Implementations

This repository features practical AutoGluon implementations across tasks like Kaggle competition solutions, tabular classification/regression, multimodal analysis, feature engineering, and multi-label classification. Each Colab notebook runs real-world datasets (text, image, time series) in Google Colab with complete outputs for reproducibility.

subhashpolisetti/RAG-LLM-VecDB-Survey

This repository explores how Large Language Models (LLMs) and Vector Databases (VecDBs) work together, based on insights from the referenced survey paper. It focuses on showing how their combination can solve practical problems, like improving how AI retrieves and uses information (retrieval-augmented generation) and building more efficient systems

subhashpolisetti/apache-beam-and-eda-projects

Apache Beam and EDA Projects: Showcasing real-time data processing with Apache Beam, interactive visualizations with D3.js, and automated EDA with Sweetviz and PyCaret. Includes Jupyter notebooks and outputs for learning and exploration.

subhashpolisetti/EDA-Timeseries-Tabular

This repository contains two machine learning projects: Air Quality Prediction, which predicts CO(GT) levels using environmental and pollutant data with AutoML, and NYC Taxi Fare Prediction, predicts taxi fares based on trip data using automated machine learning. Both projects showcase data analysis,preprocessing, and predictive modeling techniques

subhashpolisetti/HoppingWindow-CrudeOil

This project analyzes West Texas Intermediate (WTI) Crude Oil Prices using a hopping window strategy to calculate weekly mean and maximum prices, offering detailed insights into price fluctuations.

subhashpolisetti/CRISPDM-SEMMA-KDD-Workflows

This repository demonstrates three data mining methodologies applied to various real-world datasets: CRISP-DM (Weather Analysis), KDD (Social Media Ads Analysis), and SEMMA (Spotify Recommendation System). Each project includes data exploration, preprocessing, modeling, and evaluation steps, along with comprehensive documentation, supporting files,

subhashpolisetti/Python-MQTT-Message-Stream

This project demonstrates asynchronous message streaming using MQTT for Internet of Things (IoT) applications. We’ll set up a Publisher and a Subscriber to handle 1,000,000 messages via the Mosquitto MQTT broker.

subhashpolisetti/MQTT-Reservoir-Data-Pipeline

California Reservoir Water Monitoring System – A data aggregation and monitoring solution using MQTT to collect and summarize daily water mark levels across California's reservoirs. This system transforms CSV data into JSON, generates daily reports, and provides insights into water availability.

subhashpolisetti/TimeSeriesDataAggregation

A Python project demonstrating time-series data aggregation using a hopping window function to calculate mean temperature readings from simulated sensor data. Ideal for streaming applications requiring low-latency insights over overlapping time intervals in real-time

subhashpolisetti/realtime-websocket-client

This project demonstrates a WebSocket-based real-time communication system with a client-server setup and a basic user interface. The client sends 10,000 messages to the server, which responds to each message, showcasing efficient, long-lasting, full-duplex communication.

subhashpolisetti/flask_real_chat_application

This is a real-time chat application built with Flask, Flask-SocketIO, and SQLite. Users can join chat rooms, send messages, and view message history in real-time. The app features a simple and responsive UI that provides a smooth chat experience

subhashpolisetti/Cognitive-Services-OCR-Integration

subhashpolisetti/blog-microservices-architecture

This project is a microservices-based architecture for a blog platform. It was originally a monolithic application and has been refactored into microservices for better scalability and maintainability. It includes the following microservices:

subhashpolisetti/Automated-ML-with-PyCaret

PyCaret-ML-Workflows is a comprehensive repository showcasing the power and versatility of PyCaret for machine learning tasks. This project includes various workflows for classification, regression, and clustering.

subhashpolisetti/BizCard_App

subhashpolisetti/Cart-Functionality

subhashpolisetti/OnboardingFrontend

subhashpolisetti/OnboardingBackendSpringboot

subhashpolisetti/social-media