Date: 15-03-2024
Time: 9:00 AM to 3:00 PM
Venue: LDRP-ITR
Participants: 80
Deep Dive Into Dimensionality Reduction - A Machine Learning Approach
Date: 15-03-2024
Venue: LDRP-ITR
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About the Speaker:
Dr. Mehul Raval
- Professor & Associate Dean of Experiential Learning at Ahmedabad University
Dr. Mehul Raval served as a guiding force in the workshop, leveraging his extensive expertise and academic experience to provide invaluable insights and mentorship to participants. As a respected figure in the field of Electronics and Telecommunication Engineering, with a focus on Computer Vision, Image Processing, and Machine Learning, Dr. Raval's contributions enriched the learning experience, offering practical guidance and fostering a deeper understanding of key concepts among attendees.
Jay Chaudhari
- Junior Research Fellow at Ahmedabad University
Jay Chaudhari played a crucial role in the workshop, drawing on his expertise to offer invaluable guidance and mentorship to participants. With a background in Electrical Engineering and Automatic Control & Robotics, Jay's contributions enriched the learning experience, providing practical insights and fostering a deeper understanding of key concepts among attendees.
15-03-2024At: LDRP-ITR
About the Event :
This one-day hands-on workshop on Machine Learning, Driven by an unwavering commitment to empower students of the 6th Semester with practical skills and profound insights, this meticulously crafted session aimed to transcend traditional learning boundaries and embrace the transformative power of experiential education.
By immersing students in interactive learning experiences, the workshop sought to cultivate a deeper understanding of machine learning methodologies, equipping them with the tools and knowledge essential for success in today's data-driven world.
The workshop provided diverse benefits, equipping participants with qualitative knowledge and practical insights into Machine Learning. Beyond theory, attendees forged industrial connections and formed a strong peer network. They also gained insights into real-world ML applications, enhanced problem-solving skills, and deepened their understanding of ML algorithms' mathematical foundations.
Glimpse of the Event :
