SASANK YENDURI

Facility: Health Provider Life Sciences: The Process Include acquiring data, storing it and transforming the data using the designed mapping rules into the clients required dashboards design. The acquiring and storing is done using Azure blob and Snowflakes. The data was pushed onto DBT and transformed the data into SQL models as per the mapping rules designed before. The final schema is designed in snowflake and using that the tableau dashboards are designed as per the requirement. Facility: Migrators and Accelerators: Worked on the python programs of migrator where the connection strings of source and destination logic has to be implemented. This is followed by testing of the migrator locally and then by using Telnet application (putty), connected to the server and started installing the required packages, libraries including postgres db for the Migrator. This entire deployment and hosting are being taken care by the cloud provider - azure. Facility: Alzheimer's Disease Predictions: Followed the Traditional ML Pipeline-- Acquired the Data from OASIS Brains. Data Preprocessed-Handled all the missing values. EDA - Visualized all the relations between features. Feature Selection - Selected K best features - Chi2 Testing. Feature Scaling - StandardScaler. Model Creation-SVM. Web Framework -- Django framework.

Worked in Multiple role which includes Front end, Analyst, ML Engineer. Primarily designed an algorithm for grocery prediction using ML and designed a basic form in the front end which takes a customer input for the recommendations of other groceries. Involved in front end development of forms in a project.