- Neural Networks seem to follow a puzzlingly simple strategy to classify images - Mar 5, 2019.
We explain why state-of-the-art Deep Neural Networks can still recognize scrambled images perfectly well and how this helps to uncover a puzzlingly simple strategy that DNNs seem to use to classify natural images.
Classification, Deep Learning, Deep Neural Network, ICLR, Image Classification, ImageNet, Neural Networks
- Deep Multi-Task Learning – 3 Lessons Learned - Feb 15, 2019.
We share specific points to consider when implementing multi-task learning in a Neural Network (NN) and present TensorFlow solutions to these issues.
Deep Learning, Deep Neural Network, Machine Learning, Neural Networks, Optimization, TensorFlow
Top 8 Free Must-Read Books on Deep Learning - Apr 10, 2018.
Deep Learning is the newest trend coming out of Machine Learning, but what exactly is it? And how do I learn more? With that in mind, here's a list of 8 free books on deep learning.
Deep Learning, Deep Neural Network, Free ebook, Machine Learning, Neural Networks
- Tensorflow Tutorial: Part 1 – Introduction - Sep 21, 2017.
Everyone is talking about Tensorflow these days. In this multipart series, we explain Tensorflow in detail, including it’s architecture and industry applications.
Deep Learning, Deep Neural Network, Machine Learning, Neural Networks, TensorFlow
- 3 practical thoughts on why deep learning performs so well - Feb 3, 2017.
Why does Deep Learning perform better than other machine learning methods? We offer 3 reasons: integration of integration of feature extraction within the training process, collection of very large data sets, and technology development.
Big Data, Convolutional Neural Networks, Deep Learning, Deep Neural Network, Feature Extraction, Recurrent Neural Networks
6 areas of AI and Machine Learning to watch closely - Jan 25, 2017.
Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.
AI, Deep Neural Network, Generative Adversarial Network, Machine Learning, Reinforcement Learning
- Deep Learning cleans podcast episodes from ‘ahem’ sounds - Nov 8, 2016.
“3.5 mm audio jack… Ahem!!” where did you hear that? ;) Well, this post is not about Google Pixel vs iPhone 7, but how to remove ugly “Ahem” sound from a speech using deep convolutional neural network. I must say, very interesting read.
Convolutional Neural Networks, Deep Learning, Deep Neural Network, Neural Networks, Podcast, Speech
- 3 Thoughts on Why Deep Learning Works So Well - Aug 10, 2016.
While answering a posed question in his recent Quora Session, Yann LeCun also shared 3 high-level thoughts on why deep learning works so well.
Convolutional Neural Networks, Deep Learning, Deep Neural Network, Neural Networks, Quora, Yann LeCun
- Stochastic Depth Networks Accelerate Deep Network Training - Apr 7, 2016.
Read about the presentation and overview of a new deep neural network architectural method, and the response to some strong reaction that it brought about.
Architecture, Deep Learning, Deep Neural Network, Machine Learning
- Beyond the Fence, and the Advent of the Creative Machines - Jan 25, 2016.
Creative machines have been making their influence felt for some time, but an upcoming stage production challenges preconceived notions of what art is.
Pages: 1 2
AI, Art, Deep Neural Network, Matthew Mayo
- Deep Forger: Art Forgery Meets Deep Neural Nets - Dec 1, 2015.
The past year has seen deep learning make exceptional advances in imaging, perhaps most notably with Google's Deep Dream. See how a clever Twitter bot employs deep neural nets to paint images in the style of famous painters.
Pages: 1 2
Art, Deep Learning, Deep Neural Network, Matthew Mayo
- Why Does Deep Learning Work? - Jun 23, 2015.
Many researchers recently trying to open the “black-box” of the deep learning. Here we summarize these efforts of how neural nets of deep learning are evolve and how Spin Funnel and deep learning are related.
Deep Learning, Deep Neural Network, Neural Networks
- The Myth of Model Interpretability - Apr 27, 2015.
Deep networks are widely regarded as black boxes. But are they truly uninterpretable in any way that logistic regression is not?
Deep Learning, Deep Neural Network, Interpretability, Support Vector Machines, Zachary Lipton
- Juergen Schmidhuber AMA: The Principles of Intelligence and Machine Learning - Mar 9, 2015.
Jürgen Schmidhuber, pioneer in innovating Deep Neural Networks, answers questions on open code, general problem solvers, quantum computing, PhD students, online courses, and the neural network research community in this Reddit AMA.
AI, Deep Learning, Deep Neural Network, Human Intelligence, Jurgen Schmidhuber, PhD, Python, Quantum Computing, Reddit
- Deep Learning can be easily fooled - Jan 14, 2015.
It is almost impossible for human eyes to label the images below to be anything but abstract arts. However, researchers found that Deep Neural Network will label them to be familiar objects with 99.99% confidence. The generality of DNN is questioned again.
Deep Learning, Deep Neural Network, Evolutionary Algorithm, Image Recognition, Ran Bi
