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MeetAI Engineer
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Meet Nagadia is a dedicated and skilled AI and Machine Learning Engineer with a strong academic background and extensive professional experience. With a Master's degree in Artificial Intelligence and a Bachelor's degree in Information Technology, Meet brings a deep understanding of cutting-edge technologies and their practical applications. With a proven track record in developing innovative solutions, Meet has led successful projects in various domains, including e-commerce, email filtering, and recommendation systems.
As an AI Engineer at CoutLoot, Meet led the development of pioneering solutions like VITON, a personalized outfit recommendation system, and a Blind Image Quality Assessment module, showcasing expertise in TensorFlow, GANs, and OpenCV. Prior to this, Meet honed skills in machine learning and natural language processing at DeftBOX Solutions, where contributions included enhancing topic modeling accuracy and architecting NLP-based recommendation systems.
Meet's project portfolio demonstrates proficiency in computer vision, deep learning, and data analysis, as showcased in projects like the Leaf Disease Detector and Market Basket Analysis. With expertise in Python, TensorFlow, PyTorch, and scikit-learn, Meet excels in designing and implementing robust AI solutions.
With a passion for teaching and sharing knowledge, Meet is keen on opportunities to mentor students in AI and ML, providing guidance in assignments, projects, and practical applications. With a commitment to excellence and a collaborative approach, Meet is dedicated to fostering learning and driving innovation in the field of artificial intelligence and machine learning.
Subjects
Python Beginner-Expert
Machine Learning Beginner-Expert
Artificial intelligence Beginner-Expert
Experience
AI Engineer (Oct, 2023–Present) at CoutLoot
● Led the development of an early Proof of Concept (PoC) for VITON, employing cutting-edge technologies such as TensorFlow and GAN. This system provides personalized outfit recommendations based on body types, skin tones, and occasions, contributing to a 3% boost in user engagement, even in its initial try-on sessions. ● Spearheaded the implementation of a Blind Image Quality Assessment module using TensorFlow and OpenCV, significantly improving the visual appeal of seller uploads on our platform by 8%.
ML Engineer (Dec, 2021–Jan, 2023) at DeftBOX Solutions
•Enhanced Topic Modeling accuracy by 15% through rigorous data-driven experimentation, utilizing diverse algorithms such as LDA and parameter tuning. •Additionally, architected an NLP-based recommendation system for product suggestions, achieving an impressive 68% overall accuracy. Employed cutting-edge technologies, including Python, scikit-learn, TensorFlow, and spaCy, to drive impactful results. •Optimized the Apache Airflow environment, achieving a 10% efficiency boost that significantly contributed to the project's overall development success. Fine-tuned spaCy NER Model using Prodigy, which increased the accuracy and performance by 10%.
Education
AI (Jul, 2020–May, 2022) from AURO Univeristy Surat–scored 8.8
IT (Jul, 2017–May, 2020) from B.K.Birla College of Arts Science and Commerce, Kalyan–scored 8.9