Abstract: Generative AI has revolutionized various domains, including art, music, and storytelling. In this beginner-friendly session, we will embark on a journey through the Generative AI landscape, understanding its fundamental concepts, techniques, and applications. We will explore popular generative models, such as Generative Adversarial Networks (GANs), LLMs, etc. and their role in generating realistic and creative outputs. Participants will have the opportunity to dive into hands-on activities, where they will train and deploy a generative model to generate unique pieces of art and text. By the end of this session, beginners will have a solid grasp of Generative AI, empowering them to explore its endless possibilities.
+ Gain a comprehensive understanding of Generative AI and its significance in various domains.
+ Explore popular generative models, such as GANs, LLMs and their architectures.
+ Engage in hands-on activities to create unique pieces of art using generative models.
+ Discover advanced techniques for enhancing generative models, including conditional generation, text-to-image generation, and style transfer.
+ Discuss ethical considerations and challenges associated with generative AI, including bias, fairness, and responsible AI practices.
+ Have the opportunity to ask questions and receive clarifications during the Q&A session.
By the end of the session, attendees will have a solid grasp of Generative AI, enabling them to explore its applications and unleash their creativity in their own projects.
We will leverage the python stack with libraries such as TensorFlow/PyTorch, huggingface and more
python and beginner understanding of deep learning concepts
Bio: Raghav is a seasoned Data Science professional with over a decade's experience of research & development of large-scale solutions in Finance, Digital Experience, IT Infrastructure and Healthcare for giants such as Intel, American Express, United HealthGroup and DeliverHero. He is an innovator with 7+ patents, a published author of multiple well received books & peer-reviewed papers and a regular speaker in leading conferences on topics in the areas of Machine Learning, Deep Learning, Computer Vision, NLP, Generative Models and Augmented Reality.