Synthetic data to augment under-represented classes in real datasets is natural to improve fairness. However, we have to balance distribution shift with improvement of fairness. We propose dynamic ratio adjustment of real vs synthetic data. @deanh_tw @wn8_nie @ArashVahdat
MACHINE LEARNING
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Neural Operators: Discretization Invariance for Variable Resolutions
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Interesting @smnlssn I encourage you to explore neural operators since they will provide discretization invariance and can handle different resolutions directly.
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5 Ways To Implement AI In Your Business Strategy
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5 Ways To Implement AI In Your Business Strategy
#AI #AIio #BigData #ML #NLU #Futureofwork @TopCyberNews @SpirosMargaris @MarshaCollier @MHiesboeck
@MHcommunicate @Fisher85M @MikeQuindazzi @NealSchaffer
http://
ow.ly/71Qa30svtqv -
Your Guide to AI June 2023
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Link below: https://
open.substack.com/pub/nathanbena
ich/p/your-guide-to-ai-june-2023?r=iksr&utm_medium=ios&utm_campaign=post
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Anatomy of Autonomy: AI Agents as the Next Killer App
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The Anatomy of Autonomy: Why Agents are the next AI Killer App after ChatGPT https://
bit.ly/3OnxLez #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Deep Learning for Computer Vision Course by Justin Johnson
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Deep Learning for Computer Vision.
University of Michigan. EECS 498-007 / 598-005
Justin Johnson A deep dive into neural-network-based DL methods for CV, focusing on training and debugging neural networks and understanding cutting-edge research. https://
youtube.com/playlist?list=
PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r
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Full Stack Deep Learning UC Berkeley Spring 2021 Online Course
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Full Stack Deep Learning
UC Berkeley Spring 2021 Online Course
Sergey Karayev, Josh Tobin, and Pieter Abbeel Training models is just one part of shipping a deep learning project. This course teaches full-stack production deep learning. https://
fullstackdeeplearning.com/spring2021/ -
Applied Machine Learning Course Cornell Tech CS 5787
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Applied Machine Learning
Cornell Tech CS 5787
Volodymyr Kuleshov A machine learning introductory course that starts from the very basics, covering all of the most important machine learning algorithms and how to apply them in practice. https://
youtube.com/playlist?list=
PL2UML_KCiC0UlY7iCQDSiGDMovaupqc83
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Deep Neural Networks Design Principles UC Berkeley Course
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Designing, Visualizing, and Understanding Deep Neural Networks
UC Berkeley CS L182
John Canny A theoretical course focusing on design principles and best practices for designing deep neural networks. https://
bcourses.berkeley.edu/courses/1487769 -
NYU Deep Learning Course by LeCun and Canziani
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Deep Learning
NYU DS-GA 1008
Yann LeCun and Alfredo Canziani This course covers the latest techniques in deep learning and representation learning with applications to computer vision, natural language understanding, and speech recognition. https://
atcold.github.io/pytorch-Deep-L
earning/
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