This blog summarizes Andrew Ng's advice on how to read research papers and explore a machine learning career from his lecture in the Stanford CS230 Deep learning course.
ByMohamed Ali Habib
January 29, 2021
Dr. Ji Liu shared his research experience in deep learning and as an assistant professor and Director at Kuaishou AI Labs
Dr. Le Lu shared his insights on modern medical imaging, his work at PAII Inc. and the future of deep learning in medical research.
Dr. Hua shared inspiring thoughts on the trends and challenges of computer vision and the future of Artificial Intelligence.
Exclusive interview at NeurIPS 2019 about European Lab for Learning & Intelligent Systems (ELLIS) with Nuria Oliver.
Max Weiling of University of Amsterdam and VP of Technologies at Qualcomm Netherlands goes over some insights on machine learning, computing, AI, and more.
This blogs features NeurIPS 2019 Outstanding New Directions Paper Award winners, Vaishnavh Nagarajan and J. Zico Kolter. They explain how negative results showing that many existing bounds on the performance of deep learning algorithms don’t do what they claim.
Importance and limitations of data privacy, and the past and future of machine learning.
Graph Neural Networks (GNNs) has seen rapid development recently. This blog provides a quick introduction to the methodology and summarizes some of the latest research on GNNs from top AI conferences.
This article looks into a new ECCV 2020 paper "Rewriting A Deep Generative Model" that enables direct editing of the GAN model to provide the desired output even if it does not match the dataset.
October 1, 2020
The 2019 AI Commercialization Conference features renowned AI tech leaders with extensive industry experience as guest speakers and a live panel discussion where they share their insight on the future of transportation.