Bidyarani Sabat

Experienced IT professional with experience in Kubernetes and AWS services.

Proficient with container systems like Docker and container orchestration like EKS container service, Kubernetes. Managed Docker containerization and Docker orchestration using Kubernetes.

Have good knowledge of AWS services like EC2, VPC, S3, IAM, Load Balancing, Auto scaling and Security groups other services in AWS.

Experienced with Jenkins-based CI/CD pipelines, automating builds and deployments using Groovy scripts.

Experienced in managing Git repositories, access control, branching strategies, troubleshooting Git issues, and repository maintenance.

Experience with End-to-end release lifecycle management, coordinating deployments, managing release calendars, ensuring IT governance compliance, and documenting rollback procedures.

Datamites, Training, 10/01/23, 02/29/24

Cellphone Price Prediction, 

Developed a machine learning model to predict cellphone prices based on features like brand, tech specifications, and market trends, aiming to provide actionable insights for potential buyers and sellers Utilized Python, pandas for data manipulation, scikit-learn for model building, and matplotlib for data visualization. Achieved a model accuracy of 90% on the testing dataset; insights were used to create a user-friendly price recommendation tool that helps users determine fair market prices for cellphones. Insurance Cost Prediction, 

Datamites, Training, 10/01/23, 02/29/24, 

Gathered data from multiple sources, ensuring accuracy and usability by cleaning and preprocessing the data. Applied linear regression techniques to create a predictive model; performed feature selection and model tuning to enhance prediction accuracy. Analyzed model outputs to derive actionable insights and presented findings through detailed visualizations. Skin Disorder Identification, 

Datamites, Training, 10/01/23, 02/29/24, 

Created a machine learning model to accurately identify and classify various skin disorders using a dataset of dermatological images. Utilized Python for data preprocessing and augmentation to enhance model training effectiveness. Implemented convolutional neural networks (CNNs) with TensorFlow.

• Odia
• Hindi
• English