Projects

Harnessing technology to transcend language barriers

Web Application Development with a Jenkins Pipeline Triggered by GitHub Web-hook Integration

Ansible, Git, Unix Shell, Docker, Jenkins, VS Code, HTML/CSS.

The project aims to automate the building, testing, and deployment process of a web application using Jenkins and GitHub. The Jenkins pipeline will be triggered automatically by GitHub web-hook integration when changes are made to the code repository. The pipeline will include stages such as building, testing, and deploying the application.

Deploying web app using Jenkins CI/CD declarative pipeline

Ansible, Git, Unix Shell, Docker, Jenkins, VS Code, Kubectl

The project is about automating the deployment process of a web application using Jenkins and its declarative syntax. The pipeline includes stages like building, testing, and deploying to a staging environment. It also includes running acceptance tests and deploying to production if all tests pass.

Deploying a Multi-Tier Website Using AWS EC2

EC2 Instanc, AutoScaling and RDS Instance

Amazon Elastic Compute Cloud (Amazon EC2) provides scalable computing capacity in the Amazon Web Services (AWS) cloud. Using Amazon EC2 eliminates your need to invest in hardware up front so you can develop and deploy applications faster. You can use Amazon EC2 to launch as many or as few virtual servers as you need, configure security and networking, and manage storage. Amazon EC2 enables you to scale up or down to handle changes in requirements or spikes in popularity, reducing your need to forecast traffic.

Data Collection and Data management and verification using Python, Shell Script

While several datasets for autonomous navigation have become available in recent years, they tend to focus on structured driving environments. This usually corresponds to well-delineated infrastructure such as lanes, a small number of well-defined categories for traffic participants, low variation in object or background appearance and strict adherence to traffic rules. We propose IDD, a novel dataset for road scene understanding in unstructured environments where the above assumptions are largely not satisfied.
For more than 20 years, IIIT-Hyderabad (IIITH) has been dedicated to enhancing the quality of education in cutting-edge areas of Artificial intelligence (AI) and Machine Learning (ML) through strong research programs in machine learning, image processing, computer vision, robotics, natural language processing, pattern recognition, and speech processing. IHub-Data, IIIT-Hyderabad is one of the 25 Technology Innovation Hubs (TIHs) established under the National Mission on Interdisciplinary Cyber - Physical Systems (NM-ICPS) by DST, Government of India.

Data Collection and Data management and verification using Python, Shell Script

At IIIT Hyderabad, we recorded 660.5 hours of data with the help of 138 subjects. The videos were collected in 5 different states in India, geographically well apart. We cover 36 different scenarios, such as making bricks using hands, knitting, making egg cartons, and hairstyling. The age of subjects ranged from 18-84 years with 10 distinct professional backgrounds teachers, students, farmers, blacksmiths, homemakers, etc. Out of all the subjects, 94 were males, and 44 were females. We use GoPro Hero 6 and GoPro Hero 7 for recording the videos. The GoPro’s were shipped to the participants in different parts of the country. Videos were shared back either in external hard disks or over the cloud storage. Each video was manually inspected for any sensitive content before sharing.

HTML, CSS, JavaScript, Python, Django, VS Code

Developed and maintained a complex web application using Python, Django, and related technologies, resulting in a 25% increase in user engagement and a 20% increase in revenue within the first year.
Wrote custom Python code to extend Django applications, resulting in a 30% reduction in development time and a 15% increase in overall code quality.
Collaborated with other developers, designers, and stakeholders to integrate third-party services and APIs, resulting in a 40% increase in application functionality and user satisfaction.
Created and maintained automated unit and integration tests, reducing bug-related delays by 40% and improving overall code quality by 15%.