- Top KDnuggets tweets, Nov 10-16: 5 Books Every #Data Professional Needs; TensorFlow Disappoints – Google Deep Learning falls shallow - Nov 17, 2015.
Deep Learning for #Visual Question Answering; 5 Books Every #Data Professional Needs; Deep, excellent overview: A Statistical View of #DeepLearning; TensorFlow Disappoints - Google #DeepLearning falls shallow.
- Understanding Convolutional Neural Networks for NLP - Nov 11, 2015.
Dive into the world of Convolution Neural Networks (CNN), learn how they work, how to apply them for NLP, and how to tune CNN hyperparameters for best performance.
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- Deep Learning Finds What Makes a Good #selfie - Oct 28, 2015.
Ever wonder how a convolutional neural network would rate your selfies? Well, wonder no more!
- Top /r/MachineLearning Posts, June: Neural Network Generated Images, Free Data Science Books, Super Mario World - Jul 2, 2015.
Generating images with neural networks, free data science books, machine learning for playing Mario, implementing neural networks in Python, and video generation based on terms were all covered this month on /r/MachineLearning.
- Popular Deep Learning Tools – a review - Jun 18, 2015.
Deep Learning is the hottest trend now in AI and Machine Learning. We review the popular software for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch.
- Top /r/MachineLearning Posts, Mar 29-Apr 4: Andrew Ng AMA, Deep Learning for NLP, and OpenCL Convnets - Apr 10, 2015.
Andrew Ng's upcoming AMA, scikit-learn updates, Richard Socher's Deep Learning NLP videos, Criteo's huge new dataset, and convolutional neural networks on OpenCL are the top topics discussed this week on /r/MachineLearning.
- Inside Deep Learning: Computer Vision With Convolutional Neural Networks - Apr 9, 2015.
Deep Learning-powered image recognition is now performing better than human vision on many tasks. We examine how human and computer vision extracts features from raw pixels, and explain how deep convolutional neural networks work so well.
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- Talking Machine – 3 Deep Learning Gurus Talk about History and Future of Machine Learning, part 1 - Mar 25, 2015.
An recent interview from the talking machine podcast with three deep learning experts. They talked about the neural network winter and its renewal.
- Do We Need More Training Data or More Complex Models? - Mar 23, 2015.
Do we need more training data? Which models will suffer from performance saturation as data grows large? Do we need larger models or more complicated models, and what is the difference?
- Deep Learning for Text Understanding from Scratch - Mar 13, 2015.
Forget about the meaning of words, forget about grammar, forget about syntax, forget even the very concept of a word. Now let the machine learn everything by itself.
- (Deep Learning’s Deep Flaws)’s Deep Flaws - Jan 26, 2015.
Recent press has challenged the hype surrounding deep learning, trumpeting several findings which expose shortcomings of current algorithms. However, many of deep learning's reported flaws are universal, affecting nearly all machine learning algorithms.
- Deep Learning Wins Dogs vs Cats competition on Kaggle - Feb 5, 2014.
A Deep learning expert wins Kaggle Dogs vs Cats image competition with an almost perfect result.