All lectures and hands-on sessions will be conducted in online mode only!!
Announcements !
We have sent the mail containing the Zoom class links for the WSDL 2023: Advance Course as well as the google classroom invite. If you are still having any issue, mail us at ecsu.wsdl2023@gmail.com
We will set up a help desk for your convenience on 20th of January, 2023 (Friday) from 4:00 PM to 5:00 PM. The google meet meeting link for the help desk is: https://meet.google.com/bbe-ssgk-grg
We have sent the registration confirmation mail containing the registration id, and the mail containing the Zoom class links for the WSDL 2023: Basic Course as well as the google classroom invite. If you are still having any issue, mail us at ecsu.wsdl2023@gmail.com
News
WSDL 2023: Plenary Talk on "Fairness ML" by Timnit Gebru on Feb 26th 2023- 10:00 AM :
https://youtube.com/live/INfNf7bblds?feature=shareWSDL 2023 Inauguration Lecture by Prof. Geoffrey E. Hinton
https://youtu.be/10LeyVs5pXI
Witness The Stars Align
Dr. Laurens van
der Maaten
Prof. Gérard
Biau
Prof. Mikhail
Belkin
Prof. Leman
Akoglu
Dr. Timnit
Gebru
Dr. Thomas
Kipf
The inaugural lecture will be by Prof. Geoffrey E. Hinton, Turing award winner (2018) for his foundational research that laid the foundation of deep learning.
The following visionary plenary speakers of the school continue to inspire researchers across the world. Dr. Diederik P. Kingma (Google Brain), developed the Adam optimizer, and Variational Autoencoders. Prof. Gérard Biau (Sorbonne University), directed key research in Random Forests and learning in Hilbert Spaces. Prof. Mikhail Belkin (UCSD), led the developments of Laplacian Eigenmaps, Graph and Manifold Regularizers, and Spectral Clustering. Dr. Laurens Van Der Maaten (FAIR), created the dimensionality reduction method 't-SNE'.
Welcome to the 2nd Winter School on Deep Learning
The Winter School on Deep Learning 2023 (WSDL 2023) offers self-motivated students in-depth knowledge and exposure to research in Deep Learning, organized by the Electronics and Communication Sciences Unit, at the Indian Statistical Institute, Kolkata.
The school offers hands-on courses to apply the latest Deep Learning methods to real-world problems. The school also cover the essential concepts of deep learning and the fundamentals of mathematics and programming.
Come join us as we take the journey from Perceptrons to Diffusion Models!
Scope
Participants will learn from the basics of machine learning to the advanced deep learning-based approaches with application to Computer Vision and Natural Language Processing.
Lectures will be delivered by renowned faculties and scientists (from esteemed academic and industrial organizations around the world) who have made significant contributions in their areas of research.
The lectures will be supplemented by detailed hands-on sessions.
Audience
Currently enrolled in research/project scholars, masters and final-year bachelors students.
Academics and industry Professionals.