Bhuvaneshwari U

PROFESSIONAL OBJECTIVE :

To be associated with a progressive organization that gives scope to update my skills according to latest trends and to be a part of the team that dynamically works towards growth of the organization.

PROJECTS IN IT:

Project content for data analysis in weather sets

• Data Collection: Explanation of the data sources and their characteristics Description of the data collection process and any data cleaning or preprocessing steps that were performed Overview of the data structure and variables
• Exploratory Data Analysis: Visualizations and statistical summaries of the data Identification of any patterns, trends, or anomalies in the data Analysis of the relationships between different variables
• Feature Engineering: Creation of new features from the existing data Explanation of the feature selection process and its rationale 
• Modeling: Description of the modeling techniques used, including any machine learning algorithms or statistical models Evaluation of the model performance and any model tuning that was performed
• Results and Conclusions: Presentation of the key findings and insights from the analysis Discussion of the limitations and implications of the results Suggestions for further research or improvements to the analysis .
• Conducted data analysis on weather datasets using Python, including data cleaning, feature engineering, and statistical modeling Developed and implemented machine learning models to predict weather patterns and anomalies.
• Collaborated with cross-functional teams to communicate findings and insights, and provided recommendations for improvements to weather forecasting processes .
• Maintained and updated data repositories and documentation, ensuring data quality and integrity Developed automated reports and dashboards to track key performance indicators and provide insights to stakeholders at Science Weather set.
• Monitored AWS workloads using Cloud watch to improve the visibility of workloads. Also created dashboards, setting up alarms and notifications with SNS, collecting logs for insights, and integrated with Third-party ticketing and monitoring tools.
• Implementation of Auto scaling for instances under ELB using ELB health checks.
• To create a webpage for adding customized languages needed.