AI/ML intern with experience in video analytics, facial recognition, computer vision, NLP, and machine learning model development. Has worked on research, prototype model building, data preprocessing, ETL, dashboards, an…
AI/ML intern with experience in video analytics, facial recognition, computer vision, NLP, and machine learning model development. Has worked on research, prototype model building, data preprocessing, ETL, dashboards, and deployment-related tools including Docker, Kubernetes, Flask, Django, AWS, and Streamlit.
Conducting research and development in AI/ML for Video Analytics projects with diverse applications.
Building prototype models capable of multi-face detection and person recognition.
Leveraging state-of-the-art models like FaceNet and YOLO in the computer vision domain.
Making documentation of learnings, use case reviews, findings, and key points for research of built models.
Assisted in developing and implementing a facial recognition model using a CNN pre-trained library for a security application.
Helped fine-tune the model using data augmentation and super-resolution techniques.
Performed image preprocessing to enhance model performance.
Worked with YAML files for video analytics projects.
Performed data extraction and collection using BeautifulSoup library.
Gained exposure to containerization techniques like Docker and Kubernetes to build and manage a machine learning pipeline for deployment.
Used Python frameworks like Flask and Django for web application development.
Developed an end-to-end SMS/email spam classification model using Naive Bayes.
Achieved 97.8pct accuracy and an exceptional precision score.
Applied NLP techniques during data preprocessing to improve performance.
Used MySQL for ETL and PowerBI for making dashboards.
Performed sentiment analysis and review prediction.
Conducted exploratory data analysis to uncover trends, patterns, and insights from large datasets using Python libraries such as pandas, numpy, and seaborn.
Applied several machine learning algorithms to improve model accuracy.
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