A Deep Dive into NLP with PyTorch.
how to implement more advanced architectures and apply it to real world datasets.
how to implement more advanced architectures and apply it to real world datasets.
NeurIPS | 2019
Thirty-third Conference on Neural Information Processing Systems - Accepted Competitions
Thirty-third Conference on Neural Information Processing Systems - Accepted Competitions
MIT Release New AI Programming Language Called ‘GEN’. New AI programming language goes beyond deep learning. General-purpose language works for computer vision, robotics, statistics, and more.
More information available at MIT website:
http://news.mit.edu/2019/ai-programming-gen-0626
Source code available at:
https://probcomp.github.io/Gen/
http://news.mit.edu/2019/ai-programming-gen-0626
Source code available at:
https://probcomp.github.io/Gen/
MIT News
New AI programming language goes beyond deep learning
MIT researchers’ probabilistic programming system, Gen, is making it easier for novices to get their feet wet with artificial intelligence, while also helping experts advance the field.
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Centre for Computational Statistics and Machine Learning from UCL's Machine Learning Summer School (MLSS'19) video lectures
The topics range from optimization and Bayesian inference to deep learning, reinforcement learning, and Gaussian processes. The lectures are of tutorial style, starts from basics, but then quickly picking up the pace so that after 2-4 hours of teaching, they arrive at the state of the art in the subject area.
The topics range from optimization and Bayesian inference to deep learning, reinforcement learning, and Gaussian processes. The lectures are of tutorial style, starts from basics, but then quickly picking up the pace so that after 2-4 hours of teaching, they arrive at the state of the art in the subject area.
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Heartrate - real-time visualization of code execution. Observe your Python code with this tool. Python 3.5+
How to drive #Weights and #Biases matrices in #Neural_Networks for #Machine_Learning.
Code available at:
https://github.com/yasser64b/Machine-Learning-
Code available at:
https://github.com/yasser64b/Machine-Learning-
GitHub
GitHub - yasser64b/NN-basics: Machine Learning - Activation functions -Cost Functions _Weights Biases
Machine Learning - Activation functions -Cost Functions _Weights Biases - yasser64b/NN-basics
Let your machine play Super Mario Bros! and remind our youth.
Here is python implementation of Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros.
Here is python implementation of Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros.
Github repo:
https://github.com/vietnguyen91/Super-mario-bros-A3C-pytorch?fbclid=IwAR2H1BMV24t2d2VFr4QhxIEJ21jpgtTN7ev2IlAe_ledTM3msuBzhph4P2Q
Youtube demo:
https://www.youtube.com/watch?v=YdKz1eBv1kc&feature=youtu.be&fbclid=IwAR1eXCi43R9cwS7Kk5s49Aq0VOXJik-lzFxyL_JgyuaC9jTnkCIqOdkHV14
https://github.com/vietnguyen91/Super-mario-bros-A3C-pytorch?fbclid=IwAR2H1BMV24t2d2VFr4QhxIEJ21jpgtTN7ev2IlAe_ledTM3msuBzhph4P2Q
Youtube demo:
https://www.youtube.com/watch?v=YdKz1eBv1kc&feature=youtu.be&fbclid=IwAR1eXCi43R9cwS7Kk5s49Aq0VOXJik-lzFxyL_JgyuaC9jTnkCIqOdkHV14
GitHub
GitHub - vietnh1009/Super-mario-bros-A3C-pytorch: Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros - vietnh1009/Super-mario-bros-A3C-pytorch
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Let's have a little fun. World of Machine Learning, Deep Learning, Python with frameworks
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From ICCV 19: PIFu, an end-to-end deep learning method that can reconstruct a 3D model of a person wearing clothes from a single image.