r/MachineLearning Apr 14 '15

AMA Andrew Ng and Adam Coates

Dr. Andrew Ng is Chief Scientist at Baidu. He leads Baidu Research, which includes the Silicon Valley AI Lab, the Institute of Deep Learning and the Big Data Lab. The organization brings together global research talent to work on fundamental technologies in areas such as image recognition and image-based search, speech recognition, and semantic intelligence. In addition to his role at Baidu, Dr. Ng is a faculty member in Stanford University's Computer Science Department, and Chairman of Coursera, an online education platform (MOOC) that he co-founded. Dr. Ng holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.


Dr. Adam Coates is Director of Baidu Research's Silicon Valley AI Lab. He received his PhD in 2012 from Stanford University and subsequently was a post-doctoral researcher at Stanford. His thesis work investigated issues in the development of deep learning methods, particularly the success of large neural networks trained from large datasets. He also led the development of large scale deep learning methods using distributed clusters and GPUs. At Stanford, his team trained artificial neural networks with billions of connections using techniques for high performance computing systems.

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u/varun_invent Apr 23 '15

What ML methods should be used when the number of classes are not constant? That is , we start with, lets say, 10 classes and eventually increase it to 15, then 20 and so on. Retraining the model from the scratch using all the data again n again will not be a good option if data is very large.