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Two Minute Papers: AI Learns Real-Time Defocus Effects in VR

The paper “DeepFocus: Learned Image Synthesis for Computational Displays” and its source code is available here: DeepFocus: Learned Image Synthesis for Computational Displays https://www.oculus.com/blog/introducing-deepfocus-the-ai-rendering-system-powering-half-dome/ https://github.com/facebookresearch/DeepFocus Pick up cool perks on our Patreon page: › https://www.patreon.com/TwoMinutePapers We would like to thank our generous Patreon supporters who make Two Minute Papers possible: 313V, Alex Haro, Andrew Melnychuk, […]
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Two Minute Papers: Computer Games Empower Deep Learning Research | Two Minute Papers #105

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Two Minute Papers: Image Matting With Deep Neural Networks | Two Minute Papers #209

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Two Minute Papers: Verifying Mission-Critical AI Programs | Two Minute Papers #179

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Top Kaggle Solution for Fall 2021 Semester

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Deep Learning Basics: Introduction and Overview

An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entire new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, […]
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Robert Lange on NN Pruning and Collective Intelligence

We speak with Robert Lange! Robert is a PhD student at the Technical University Berlin. His research combines Deep Multi-Agent Reinforcement Learning and Cognitive Science to study the learning dynamics of large collectives. He has a brilliant blog where he distils and explains cutting edge ML research. We spoke about his story, economics, multi-agent RL, […]
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Lecture 0 | Course Logistics

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 Slides: http://deeplearning.cs.cmu.edu/slides… For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Course Logistics YouTube Source for this AI Video
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Reinforcement Learning in the OpenAI Gym (Tutorial) – SARSA

When we last left off, we covered the Q learning algorithm for solving the cart pole problem from the OpenAI Gym. Related to Q learning is the SARSA algorithm, which also performs quite well. SARSA differs from Q learning in that it is an on policy, rather than off-policy reinforcement learning algorithm. In this video, […]
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Reinforcement Learning in Continuous Action Spaces | DDPG Tutorial (Tensorflow)

Let’s use deep deterministic policy gradients to deal with the bipedal walker environment. Featuring a continuous action space and 24 elements in the observation vector, this is a perfect environment for a non trivial example of DDPG. #DDPG #BipedalWalker #DeepDeterministicPolicyGradients Learn how to turn deep reinforcement learning papers into code: Deep Q Learning: https://www.udemy.com/course/deep-q-learning-from-paper-to-code/?couponCode=DQN-OCT-21 Actor […]
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C4W4L03 Siamese Network

Take the Deep Learning Specialization: http://bit.ly/32Rqs4S Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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Lecture 19 | Representations and Autoencoders

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Representations and Autoencoders YouTube Source for this AI Video
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Dropout Regularization (C2W1L06)

Take the Deep Learning Specialization: http://bit.ly/2x5Z9YT Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video
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Lecture 13 | (2/5) Recurrent Neural Networks

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Fall 2019 For more information, please visit: http://deeplearning.cs.cmu.edu/ Contents: • Stability • Exploding/vanishing gradients • Long Short-Term Memory Units (LSTMs) and variants • Residual Networks (Resnets) YouTube Source for this AI Video
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Using K-Fold Cross Validation with Keras (5.2)

K-Fold cross validation is an important technique for deep learning. This video introduces regular k-fold cross validation for regression, as well as stratified k-fold for classification. Cross-validation can be used for a wide array of tasks, such as error estimation, early stopping, and hyper-parameter optimization. Code for This Video: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_05_2_kfold.ipynb Course Homepage: https://sites.wustl.edu/jeffheaton/t81-558/ Follow Me/Subscribe: […]
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Cascade-Correlation and Deep Learning by Scott Fahlman (Spring 2019)

This is a guest lecture by Dr. Scott Fahlman, the inventor of Cascade-Correlation. Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Spring 2019 Slides: http://deeplearning.cs.cmu.edu/slides.spring19/Cascor_Deep_Learning_v5.pdf Related works by Dr. Scott Fahlman can be found here: https://www.cs.cmu.edu/~sef/sefPubs.htm For more information, please visit: http://deeplearning.cs.cmu.edu/ Content: • Cascade Correlation Nets YouTube Source for this AI Video
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Why The Lock Down Is Your Chance to Shine | Making the Most of Your Time

Current events have forced almost all of us to stay indoors for a prolonged period of time. While the isolation and interruption to our old routine can be stressful and difficult, it’s also a huge opportunity for personal growth. We have to focus on what really matters as well as how we can get ahead […]
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Batch Norm At Test Time (C2W3L07)

Take the Deep Learning Specialization: http://bit.ly/2vBGGmD Check out all our courses: https://www.deeplearning.ai Subscribe to The Batch, our weekly newsletter: https://www.deeplearning.ai/thebatch Follow us: Twitter: https://twitter.com/deeplearningai_ Facebook: https://www.facebook.com/deeplearningHQ/ Linkedin: https://www.linkedin.com/company/deeplearningai Source of this AI Video