BHAVYA JETHWA

LinkedIn +91-954******* ad1jvk@r.postjobfree.com GitHub

Skills

• Python PySpark SQL Artificial Intelligence Machine Learning Natural Language Processing Data Science Deep Learning Neural Networks

• Amazon Web Services Cloud Computing CI/CD Git DVC

• Flask Docker Numpy Pandas Tensorflow Keras Sklearn Word2Vec OpenCV PowerBi DSA Statistics Data Analysis Experience Software Engineer Intern Konverge.Ai 01/23 - 07/23

• Worked on an Employee Retention project, designed and implemented a model using Logistic Regression with an accuracy of 89.42% with hyperparameter tuning. Increased employee retention rate to a significant 76% and reduced the average employee turnover rate to 12%.

• Worked on a car purchase prediction project, implemented Random Forest Classifier and created a model with an accuracy of 91.23%. Built an API using Flask for the user end web application, reduced the API latency by 36% and increased the efficiency by 15%. Projects

• End to end chicken disease classification : Created an user web application to predict chicken disease by analyzing a photo of the chicken’s fecal matter. Implemented convolutional neural network with VGG-16 architecture model, Achieved an accuracy of 0.94 with a loss of 0.58 with hyperparameter tuning. Containerised the application using Docker and implemented CI/CD pipeline production grade deployment on AWS with amazon EC2 instance and amazon ECR using GitHub actions. Source code

• End to end student score prediction : Created an user web application to predict the student’s subject score by uploading other parameters Used MySQL for data ingestion. Created a Linear Regression model with R2 score of 0.8908 and hyperparameter tuning and cross-validation using GridsearchCV. Containerised the application using Docker and implemented CI/CD pipeline deployment on AWS with amazon EC2 instance and amazon ECR using GitHub actions. Source code

• Driver drowsiness detection : Created a detection system that identifies key attributes of drowsiness and triggers an alert when someone is drowsy before it is too late. Used OpenCV for real time face detection to capture eye images. Used convolutional neural network model with ReLu and Softmax as activation functions and successfully achieved an accuracy of 92.36% Source code Education Bachelor of Engineering

(Electronics)

Shri Ramdeobaba College of Engineering and Management Nagpur 2020-2023 Diploma in Electrical

Engineering

Government Polytechnic Nagpur 2017-2020

Certifications

• Python (Udemy)

• Machine Learning (Internshala)

• AWS Cloud Technical Essentials (Coursera)

• AWS Fundamentals: Addressing security risks (Coursera)

• AWS Migrating to cloud (Coursera)

• Financial Management (Coursera)

• Human Resource Management (Coursera)