Modern Practices in Artificial Intelligence and Data Science
Workshop 1: Artificial Intelligence in Image Recognition
Discover how computers can learn to recognise pictures in our workshop on Image Classification with Deep Neural Networks! We'll show you how computers can learn to classify images using deep neural networks called CNNs. Explore open-source image datasets and neural network frameworks to gain hands-on experience building, training, and validating your neural networks from scratch.
Speakers
- Mehul S Raval, Professor, School of Engineering and Applied Science
- Yagnik Bhavsar, PhD Scholar
Workshop 2: Theory and Application of Graphical Models with Real-World Data
Probabilistic Graphical Models (PGMs) are an effective tool in the field of data science for modelling intricate relationships and dependencies in large datasets. This allows data scientists to derive insights and make predictions under uncertainty. By identifying the causal relationships between variables, PGMs tackle the crucial AI problem of modelling uncertainty. In order to apply PGMs to real-world issues, participants will leave this session with a theoretical understanding of Bayesian networks, probabilistic inference, parameter and structure learning, and practical application skills. To experiment with uncertainty modelling and visualising using the NetworkX and Pgmpy libraries, participants will view the demonstration and work on the "Asia Cancer" real-time dataset.
Speakers
- Dhaval Patel, Associate Professor, School of Engineering and Applied Science
- Kashish Shah, PhD Scholar
Workshop 3: Computer Vision
Computers can be taught to interpret images and videos for various purposes, such as recognising people's faces for surveillance, identifying objects, navigating autonomous vehicles, diagnosing diseases with MRI and CT, performing remote surgery, and many more. The Computer Vision area of computer science and engineering deals with such applications. In this talk, we will discuss the emerging radiomics-based MRI analysis for diagnosing brain tumours using artificial intelligence and computer vision.
Speaker
- Jayendra Bhalodiya, Assistant Professor, School of Engineering and Applied Science
Date: Tuesday, June 4, 2024
Time: 9:00 AM - 1:00 PM
Venue: School of Engineering and Applied Science, Central Campus, Ahmedabad University
