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The Text Summarization for conversation is a sophisticated tool designed to extract key insights from chat conversations quickly and efficiently. With the aim of enabling users to grasp the main idea of a conversation without reading through the entire transcript, this project leverages cutting-edge natural language processing (NLP) techniques.
This project was all about building a informational dashboard for atliq electronics to improve their business. By doing this we can find more informations from those dashboard like finance, sales, marketing, supply chain management sector. The company wants to build a dashboard in all those areas from 2018(past) to 2022(present) with the dataset. The dataset contains above 1 million rows. These dashboard are done in power BI desktop.
This Streamlit app serves as a simple tool for predicting the likelihood of heart disease based on input features. The user can input key factors such as age, sex, chest pain type, blood pressure, cholesterol level, and more. The app provides an intuitive interface with sliders and dropdowns for data input. Behind the scenes, the app employs a basic prediction model to calculate a prediction based on the input values. While the current model is simplistic, the framework allows seamless integration with more advanced machine learning models for accurate predictions.
I recently took on a web scraping project using Selenium 4 to extract data from how stat. With advanced features, I automated the process of collecting data.This saved me time and effort while providing valuable insights into the platform's content.
In this project, the performance of the students in math score is determined with the help of other features. Here, we utilize CI/CD pipelines for deploying the app in Docker.
This project utilizes Docker Compose to manage a multi-container application. The application consists of multiple containers, including a Flask app and a MongoDB database. Docker Compose allows you to define and manage the services required for your application in a single YAML file, simplifying the setup and deployment process.
Hi I am Subhaganesh I am interested towards AI technology.Now working on llm ,RAG, systematic intelligent workflows
I have Good knowledge in RAG, Langraph and LLM.
Currently working on building intelligent automation systems powered by LLMs, vector databases, and multi-agent architectures. I specialize in designing and deploying AI/ML solutions that bridge data engineering, model optimization, and workflow orchestration. My recent work includes retrieval-augmented generation (RAG) pipelines, data enrichment frameworks, and multi-agent coordination systems for enterprise-scale automation. I also focus on enhancing data governance, document processing, and decision systems using tools like LangChain, FastAPI, FAISS, Prefect, and Power BI. Driven by curiosity and precision, I aim to create scalable AI systems that convert complex data into actionable insights and business impact.
Projects
Hackathons
Certifications
Awards
I have a decent knowledge on the below mentioned skills.Which can be used in data analysis ,data modeling, model creation.
To implement my innovative ideas and creative mind towards the goal and growth of the organization and self through the data insights.
Working with all kind of new technology by continuosly learning and Having good knowledge in understanding business problem and provide growthfull solution using insights from the data.
GUVI ,IIT-Madras,chennai, IN
KCG college of Technology, chennai, IN
Promantus Inc., CH, IN
Lambda Digital Pvt. Ltd., CH, IN
Addison Co., Chennai, IN
We worked in some projects during those periods his dedication to the work was great.
Subhaganesh was very good at Handling day to day tasks and prior to time.
Handling meetings and task with a positive attitude.
CH, IN
subhaganesh5@outlook.com
+91 9710414465