pmigdal + deep-learning   302

GauravBh1010tt/DeepLearn: Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.
deep-learning  nlp  keras 
11 days ago by pmigdal
LouieYang/stroke-controllable-fast-style-transfer: Code and data for paper: https://arxiv.org/abs/1802.07101
GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.
neural-style  deep-learning 
24 days ago by pmigdal
junxiaosong/AlphaZero_Gomoku: An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
GitHub is where people build software. More than 28 million people use GitHub to discover, fork, and contribute to over 79 million projects.
reinforcement-learning  pytorch  alpha-go  deep-learning 
7 weeks ago by pmigdal
The GAN Zoo – Deep Hunt
Every week, new papers on Generative Adversarial Networks (GAN) are coming out and it’s hard to keep track of them all, not to mention the incredibly creative ways in which researchers are naming…
deep-learning  gan 
8 weeks ago by pmigdal
A guide to receptive field arithmetic for Convolutional Neural Networks
The receptive field is perhaps one of the most important concepts in Convolutional Neural Networks (CNNs) that deserves more attention from the literature. All of the state-of-the-art object…
convolution  deep-learning 
8 weeks ago by pmigdal
Hyperparticle/one-pixel-attack-keras: Keras reimplementation of "One pixel attack for fooling deep neural networks" using differential evolution on cifar10
one-pixel-attack-keras - Keras reimplementation of "One pixel attack for fooling deep neural networks" using differential evolution on cifar10
deep-learning  keras  hacking-dl 
8 weeks ago by pmigdal
How To Create A Machine Learning Framework From Scratch In 491 steps
Note: We already posted a a short post-mortem of this project on reddit about 4 months ago. This is a significantly expanded, more detailed and polished version with detailed insights, design choices…
deep-learning  programming  education2 
8 weeks ago by pmigdal
How I Shipped a Neural Network on iOS with CoreML, PyTorch, and React Native - Stefano J. Attardi
UI Engineering and Design consultant, specializing in React and React performance. Previously at Facebook and Storehouse. Winner of the first Node.js Knockout with Swarmation.com.
pytorch  deep-learning  ios 
10 weeks ago by pmigdal
Machine learning mega-benchmark: GPU providers (part 2) | RaRe Technologies
We had recently published a large-scale machine learning benchmark using word2vec, comparing several popular hardware providers and ML frameworks in pragmatic aspects such as their cost, ease of use, stability, scalability and performance.
gpu  aws  deep-learning 
11 weeks ago by pmigdal
"Grad Student Descent" - [D] How do people come up with all these crazy deep learning architectures? : MachineLearning
For the past few days, I've been reading TensorFlow source codes for some of the latest DL architectures (e.g. Tacotron, Wavenet) and the more I...
deep-learning 
11 weeks ago by pmigdal
Faster R-CNN: Down the rabbit hole of modern object detection - Tryolabs Blog
Previously, we talked about object detection, what it is and how it has been recently tackled using deep learning. If you haven’t read our previous blog post, we suggest you take a look at it before continuing.
Last year, we decided to get into Faster R-CNN, reading the original paper, and all the referenced papers (and so on and on) until we got a clear understanding of how it works and how to implement it.
deep-learning  object-detection  rcnn 
12 weeks ago by pmigdal
How to build your own AlphaZero AI using Python and Keras
The codebase contains a replica of the AlphaZero methodology, built in Python and Keras. Gain a deeper understanding of how AlphaZero works and adapt the code to plug in new games.
reinforcement-learning  deep-learning 
12 weeks ago by pmigdal
Deepfakes
reddit: the front page of the internet
deep-learning  porn  faceswap 
january 2018 by pmigdal
LSTM by Example using Tensorflow – Towards Data Science
In Deep Learning, Recurrent Neural Networks (RNN) are a family of neural networks that excels in learning from sequential data. A class of RNN that has found practical applications is Long Short-Term…
deep-learning  lstm 
january 2018 by pmigdal
My Favorite Deep Learning Papers of 2017
Here are five deep learning papers I felt rose above the rest in 2017.
deep-learning 
december 2017 by pmigdal
Learning to Segment – Facebook Research
New detection technologies will move us toward a more precise understanding of images.
deep-learning  image-segmentation 
december 2017 by pmigdal
Improving the way we work with learning rate. – techburst
Most optimization algorithms(such as SGD, RMSprop, Adam) require setting the learning rate — the most important hyper-parameter for training deep neural networks. Naive method for choosing learning…
deep-learning  learning-rate 
november 2017 by pmigdal
Understanding Hinton’s Capsule Networks. Part I: Intuition.
Last week, Geoffrey Hinton and his team published two papers that introduced a completely new type of neural network based on so-called capsules. In addition to that, the team published an algorithm…
capsnet  deep-learning  cnn 
november 2017 by pmigdal
Using deep learning for Single Image Super Resolution
We apply three different deep learning models to reproduce stare-of-the-art results in single image super resolution.
deep-learning  upscaling  upsampling 
november 2017 by pmigdal
Experiments with a new kind of convolution – Towards Data Science – Medium
There are many things that I don’t like about convolution. The biggest of them all, most of the weights particularly in later layers are quite close to zero. This tells that most of these weights…
deep-learning  convolution 
october 2017 by pmigdal
Human log loss for image classification | deepsense.ai Blog
Deep learning vs human perception: creating a log loss benchmark - my post based on @kaggle cervical cancer contest
deep-learning  log-loss  human-learning 
september 2017 by pmigdal
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