ARAVINDA REDDY M

• Proficient in designing and developing ETL pipelines for data integration and transformation.
• Good experience in using JDBC and created PYSPARK scripts to load data from RDBMS to DBFS.
• Experience in ADF data flows, SQL DB, ADLS gen2, blob storage, MySQL.
• Developed PySpark scripts using both Data frames/SQL and RDD in Spark Databricks for Data aggregation.
• Worked on poc for converting SQL script to PySpark script using azure Databricks.
• Worked on RDD's and Data Frames.
• Experienced in SQL querying, data manipulation, and performance optimization using MySQL.
• Used Spark-SQL for querying & transformation of data residing in local databases as well as data ware houses.
• Good experience in integrating AZURE DATABRICKS to Azure services like AZURE BLOB and ADLS.
• Good in adopting to new technologies and implementing them

Pragyan AI

Project Intern - 2022

• Led an audio analysis project on Emotion Speech Recognition using Librosa package in Python programming.
• Performed data preprocessing, feature engineering, and classifier training to classify speech signals and recognize emotions from audio sources using packages in Python such as soundfile, librosa.
• Developed a predictive model that determined emotions such as happiness, sadness, anger, neutral, etc.
• Delivered the presentation and results to the management and created a detailed report on the project.

Detection of Driver Drowsiness using Python - 2021

• Analyzed video sequence of four-wheeler driver to detect person's vigilance level to reduce/avoid accidents.
• Utilized 16,000 images in .png format to train & test the data science algorithm using Python program.

Face Mask Detection using Python - 2022

• Built a face mask detector model using functions in data science and ran the model on Raspberry Pi.
• Performed in-depth modeling task to classify "with mask" and "without mask" while training the model.
• Achieved a 99.29% model accuracy using MobileNetV2 algorithm compared to other data science algorithms, resulted in precise face mask detection.