Associate Software Engineer
I am a recent Computer Science Engineering graduate with a strong passion for Data Science , Artificial Intelligence and Machine Learning. Currently working at Accenture as a Packaged App Development Associate, I focus on deploying scalable AI solutions. I am skilled in Machine Learning, Deep Learning, and Natural Language Processing, with experience in Python, TensorFlow, PyTorch, MySQL, and MongoDB. With hands-on internship experience at MathWorks, Panace.ai, and Swecha, I am actively seeking opportunities to further contribute to impactful AI and Data Science projects.
MathWorks AI internship program provides hands-on MATLAB training, empowering students to tackle real-world challenges with practical AI skills.
Internship project involved developing a system to collect user-captured symptoms and registration details, stored in a database for health monitoring and facilitating doctor appointments.
The internship provided foundational knowledge in AI and ML by actively engaging in project-based learning experiences by developing rainfall data analysis dashboard.
IEEE Publication-ICETCI 2024
Python
MySQL
Machine Learning
Deep Learning
Natural Language Processing
Large Language Model
SAP Business Objects and Data Services
Pandas
NumPy
Matplotlib
Keras
Tensorflow
Opencv
Pytorch
Streamlit
Neo4j
Unstructured to Visualized | Python, Streamlit, NLP, Deep Learning, NEL API’s, REBEL, Neo4j
• Implementing advanced ML/NLP pipeline for unstructured text insights.Targeting superior relationship extraction
• Accuracy via diverse dataset evaluation.Future focus:deploying a recommendation system for enhanced usability
• Expanding into multimodal analysis and interdisciplinary fields like healthcare and finance can yield new insights and applications
Trigger Word Detection | Flask, Colab,Gaussian Mixtures, Git, Unix Shell, VS Code
• Team project for the Techolution Hackathon, earned Honorable Mention
• Developed a Application to detect the desirable trigger and take action
• Learned how to use Flask in conjunction with backend databases and APIs
Pose Detection using PoseNet | Javascript, Machine Learning, TensorFlow, Flask, OpenCV
• The project implemented a machine-learning model to accurately detect human poses in both images and videos
• Facilitating diverse applications including fitness tracking, gaming, and augmented reality