Deep LearningThis hands-on course offers a unique opportunity to dive deep into the practical aspects of building and deploying neural networks for a variety of applications. As such, it serves as a gateway to the complicated world of artificial intelligence and deep learning.
Throughout four 4-hour meetings, you will have the chance to engage in experiential learning, gaining invaluable insights into supervised and unsupervised learning techniques. From image and text classification to image generation, the students taking this course will explore the breadth of deep learning applications, guided by graduate students that expertise in this field.
Delving into a diverse array of deep learning architectures, including fully connected networks, convolutional networks, recurrent neural networks (RNN), and more, participants will gain a comprehensive understanding of the underlying principles driving AI innovation. With a focus on practical implementation, learners will harness the power of PyTorch, mastering essential skills for success in the field.
Whether you’re a novice seeking to explore the frontier of AI or a seasoned professional aiming to sharpen your skills, “A Lab in Deep Learning” promises to equip you with the knowledge and expertise needed to thrive in this rapidly evolving field.
This course is a collaboration between SIPL lab and CRML lab.
