Hi there, I'm

Sai Kumar Seela

I am a

About me

About Me

Hi, I'm Sai Kumar Seela, a B.Tech graduate in Computer Science and Engineering with a specialization in AI and ML from Vasireddy Venkatadri Institute of Technology, Guntur, where I achieved a CGPA of 8.05. I am deeply passionate about AI, Data Science, and DevOps, and I have gained hands-on experience through internships, including automating the loan approval process as a Data Science intern at Datavalley and developing a real-time fraud detection pipeline as a Machine Learning Engineer intern at iNeuron. My projects, such as the MCQs Generator Application and ISRO Video Search and Classification, showcase my expertise in leveraging AI and deep learning technologies.

Skilled in Python, Java, ReactJs, TensorFlow, AWS, Docker, and Kubernetes, I am well-equipped to tackle complex challenges in the tech industry. I also hold certifications in Full Stack Data Science, Azure AI Fundamentals, and AWS Cloud Operations, which further enhance my ability to contribute to innovative solutions in the field.

You can find my works here

View Resume Download Resume

Skills

Here are some of my skills on which I have been working for the past 2 years.

Experience

DataValley - Data Science intern

February 2024 - April 2024
- Developed a system to automate the loan approval process.
- Significantly reducing manual processing time by approximately 18 to 30 minutes per application.
- Utilized machine learning algorithms to analyze applicant data and make real-time decisions.
iNeuron - Data Science intern

January 2023 - May 2023
- Led ML project for money laundering prevention, achieving a 98.34% F1-score.
- Solve an usecase on Industry level end to end machine learning project
- ML project domain was with respect to Insurance
- Used MLOPS for building and deploying the model.
- Built CI/CD pipeline
- Used Flask Api as a backend
- Used Github actions for automatic build and deploy of the model
- Finally hosted on AWS cloud environment.
AICTE - Data Analyst Intern

March 2022 - May 2022
- Completed AWS-based data analytics internship, mastering SQL and Python.
- Conducted data cleaning and preprocessing, optimizing analysis techniques.

DataValley iNeuron AICTE

DataValley - Data Science Intern

February 2024 - April 2024

Developed a system to automate the loan approval process.
Significantly reducing manual processing time by approximately 18 to 30 minutes per application.
Utilized machine learning algorithms to analyze applicant data and make real-time decisions.

iNeuron - Data Science Intern

January 2023 - May 2023

Led ML project for money laundering prevention, achieving a 98.34% F1-score.
Solve an usecase on Industry level end to end machine learning project
ML project domain was with respect to Insurance
Used MLOPS for building and deploying the model.
Built CI/CD pipeline
Used Flask Api as a backend
Used Github actions for automatic build and deploy of the model
Finally hosted on AWS cloud environment.

AICTE - Data Analyst Intern

March 2022 - May 2022

Completed AWS-based data analytics internship, mastering SQL and Python.
Conducted data cleaning and preprocessing, optimizing analysis techniques.

Certifications

FUll Stack Data Science - iNeuron.ai

Issued on June 2024
- View Certificate
Deep Learning Foundations - iNeuron.ai

Issued on December 2022
- View Certificate
Introduction to Programming Using Python - Microsoft

Issued on June 2022
- View Certificate
AI for Everyone - Coursera

Issued on May 2022
- View Certificate
AWS Academy Machine Learning Foundations - AWS

Issued on April 2022
- View Certificate
AWS Academy Data Analytics - AWS

Issued on April 2022
- View Certificate
AWS Academy Cloud Foundations - AWS

Issued on March 2022
- View Certificate

Full Stack Data Science Deep Learning Foundations Introduction to Programming using Python AI for Everyone AWS Academy Machine Learning Foundations AWS Academy Data Analytics AWS Academy Cloud Foundations

Full Stack Data Science - iNeuron.ai

Issued on June 2024

View Certificate

Deep Learning Foundations - iNeuron.ai

Issued on December 2022

View Certificate

Introduction to Programming Using Python - Microsoft

Issued on June 2022

View Certificate

AI for Everyone - Coursera

Issued on May 2022

View Certificate

AWS Academy Machine Learning Foundations - AWS

Issued on May 2022

View Certificate

AWS Academy Data Analytics - AWS

Issued on April 2022

View Certificate

AWS Academy Cloud Foundations - AWS

Issued on March 2022

View Certificate

Projects

AP EAPCET 2024 College Selector

The AP EAPCET 2024 College Selector is a real-time web application developed using Streamlit. It aims to assist students who have qualified in the Andhra Pradesh Engineering, Agriculture and Pharmacy Common Entrance Test (AP EAPCET) in selecting the best colleges based on their preferences. This tool allows students to filter colleges according to various criteria such as location (nearby districts), desired branch of study, and other preferences.

LLM Generative AI Project using PaLM & LangChain

MCQs Generator Application

The MCQs Generator Application utilizes PaLM's advanced NLP capabilities to create over 100 contextually accurate multiple-choice questions. Built with Python, LangChain, and Streamlit, the app integrates seamlessly with the Google PaLM API to streamline content generation. This tool significantly cuts down content creation time for educators by 25%, optimizing efficiency and resource management.

E-Commerce Website using Django and React

This project is an E-Commerce website built using Django on the backend and React on the frontend. The website specializes in selling t-shirts suitable for both winter and summer seasons. It provides users with a platform to browse, search, and purchase t-shirts online.

ISRO Video Search Engine and Classification

Orbit(named it as) is a web application designed to facilitate video search and classification, specifically tailored for content relevant to the Indian Space Research Organisation (ISRO). The application employs a Long-Short Term Memory with Recurrent Convolutional Networks (LRCN) model for video classification. It supports five initial class labels: 'Animation', 'Graphics', 'IndoorControlRoom', 'OutdoorLaunchpad', and 'PersonCloseUp'. Utilizing Annoy for efficient embedding representation, the application provides users with the ten most relevant videos using Approximate Nearest Neighbors (ANN).

Scania Sensor Fault Detection

In this project, the system in focus is the Air Pressure system (APS) which generates pressurized air that are utilized in various functions in a truck, such as braking and gear changes. The datasets positive class corresponds to component failures for a specific component of the APS system. The negative class corresponds to trucks with failures for components not related to the APS system. The problem is to reduce the cost due to unnecessary repairs. So it is required to minimize the false predictions.

Money Laundering Prevention

The Project is designed to help prevent the illegal practice of money laundering using the Bitcoin blockchain transaction data. This project is aimed at providing a solution to the growing concern of illicit activities and financial crimes on the blockchain network.

Finance Complaints

By understanding existing complaints registered against financial products we can create an ML model that can help us to identify newly registered complaints whether they are problematic or not and accordingly company can take quick action to resolve the issue, and satisfy the customer's need. The problem is to identify registered complaint will be disputed by customer or not.

3D Web application(deployed using Kubernetes)

The app has multiple endpoints which you play with. The app is deployed on a Kubernetes cluster and is accessible via a LoadBalancer service.

Atliq Hardware Sales Insights (PowerBI and SQL)

The Atliq Hardware Sales Insights project uses Power BI and SQL to address declining sales and improve business performance. By integrating MySQL data with Power BI, the project provides an automated dashboard that highlights sales patterns and trends, helping the sales team make informed decisions and reduce manual data gathering time by 20%. This solution aims to boost sales, enhance financial outcomes, and optimize operational efficiency.

Store Sales Report (Airflow)

The sales report data pipeline is a workflow that uses Airflow to automate the process of generating and sending a sales report based on the input file. It involves reading and cleaning the input file, saving the cleaned data into mysql, calculating and saving the store location wise and store wise profits, and sending an email with the csv file attached

Heart Disease Prediction

Built a machine learning model for predicting heart disease using various features and data.The model can be used to predict the likelihood of a person having heart disease based on their input.The model can be deployed using BentoML, a framework for serving and managing machine learning models. The data is versioned using DVC, a tool for data and model management.

Chainlit-Zomato-GPT

It's Demo bot created for an online food ordering business. This demo was built with the help of Chainlit. Chainlit is like Streamlit for LLM app development :)