Neural Networks, Manifolds, and Topology. Deep Learning, NLP, and Representations. An Exploration of Dimensionality Reduction. Deep Learning and Human Beings. Groups and Group Convolutions. Fanfiction, Graphs, and PageRank. See the complete list of posts.
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Home - colah's blog | colah.github.io Reviews
https://colah.github.io
Neural Networks, Manifolds, and Topology. Deep Learning, NLP, and Representations. An Exploration of Dimensionality Reduction. Deep Learning and Human Beings. Groups and Group Convolutions. Fanfiction, Graphs, and PageRank. See the complete list of posts.
colah.github.io
Fanfiction, Graphs, and PageRank - colah's blog
http://colah.github.io/posts/2014-07-FFN-Graphs-Vis
Fanfiction, Graphs, and PageRank. Posted on July 6, 2014. On a website called fanfiction.net, users write millions of stories about their favorite stories. They have diverse opinions about them. They love some stories, and hate others. The opinions are noisy, and it’s hard to see the big picture. With tools from mathematics and some helpful software, however, we can visualize the underlying structure. Graph of Harry Potter Fanfiction, colored by ship. The sheer amount of fanfiction out there is rather st...
Visualizing MNIST: An Exploration of Dimensionality Reduction - colah's blog
http://colah.github.io/posts/2014-10-Visualizing-MNIST
Visualizing MNIST: An Exploration of Dimensionality Reduction. Posted on October 9, 2014. At some fundamental level, no one understands machine learning. It isn’t a matter of things being too complicated. Almost everything we do is fundamentally very simple. Unfortunately, an innate human handicap interferes with us understanding these simple things. Even very simple things become hard to understand when you do them in very high numbers of dimensions. These techniques are the basic building blocks we wil...
Conv Nets: A Modular Perspective - colah's blog
http://colah.github.io/posts/2014-07-Conv-Nets-Modular
Conv Nets: A Modular Perspective. Posted on July 8, 2014. In the last few years, deep neural networks have lead to breakthrough results on a variety of pattern recognition problems, such as computer vision and voice recognition. One of the essential components leading to these results has been a special kind of neural network called a. At its most basic, convolutional neural networks can be thought of as a kind of neural network that uses many identical copies of the same neuron. We care about the same p...
Visualizing Representations: Deep Learning and Human Beings - colah's blog
http://colah.github.io/posts/2015-01-Visualizing-Representations
Visualizing Representations: Deep Learning and Human Beings. Posted on January 16, 2015. In a previous post. We explored techniques for visualizing high-dimensional data. Trying to visualize high dimensional data is, by itself, very interesting, but my real goal is something else. I think these techniques form a set of basic building blocks to try and understand machine learning, and specifically to understand the internal operations of deep neural networks. As we dig into this, we’ll observe what I beli...
Deep Learning, NLP, and Representations - colah's blog
http://colah.github.io/posts/2014-07-NLP-RNNs-Representations
Deep Learning, NLP, and Representations. Posted on July 7, 2014. In the last few years, deep neural networks have dominated pattern recognition. They blew the previous state of the art out of the water for many computer vision tasks. Voice recognition is also moving that way. But despite the results, we have to wonder why do they work so well? One Hidden Layer Neural Networks. It’s true, essentially, because the hidden layer can be used as a lookup table. And only on that specific input. Then we can ...
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DANIEL SLATER'S BLOG: Using Net2Net to speed up network training
http://www.danielslater.net/2016/05/using-net2net-to-speed-up-network.html
Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...
DANIEL SLATER'S BLOG: June 2015
http://www.danielslater.net/2015_06_01_archive.html
Thursday, June 18, 2015. Why there is a big unsupervised learning shaped whole in the universe. Unfortunately so far we are a long way from that and the technique shown here seems trivial compared to that goal. But the goal is interesting enough that it is worth pursuing. The answer to the question "what am I asking an unsupervised network to do? An example competitive learning neural net. It is also available in C#. From random import uniform class UnsupervisedNN(object): def init (self, size of input a...
DANIEL SLATER'S BLOG: October 2015
http://www.danielslater.net/2015_10_01_archive.html
Tuesday, October 27, 2015. Even more quick summaries of research papers. Following on from part 1. Here are even more quick summaries of research papers,. Generative NeuroEvolution for DeepLearning. Uses the MNIST hand-drawn digits dataset, trains both a normal deep network and a convolutional network. HyperNEAT on it's own performs very badly. Using HyperNEAT to generate a number of layers and then backprop on the final layer is achieves 58.4% for normal ANNs. ES-HyperNeat uses the connection weights va...
DANIEL SLATER'S BLOG: August 2015
http://www.danielslater.net/2015_08_01_archive.html
Saturday, August 29, 2015. Presenting WikiDataDotNet - Client API for WikiData. Is one of those things that sets the mind boggling at the possibilities of the internet. It's a project, started by the WikiMedia foundation, to collect structured data on everything. If you are doing anything related to machine learning, it is the best source of data I have so far found. Https:/ www.wikidata.org/w/api.php? This will return a JSON file with sections like:. Here we see the id of the item, in this case Q38.
DANIEL SLATER'S BLOG: May 2016
http://www.danielslater.net/2016_05_01_archive.html
Thursday, May 26, 2016. Using Net2Net to speed up network training. When training neural networks there are 2 things that combine to make life frustrating:. Neural networks can take an insane amount of time of train. If a network could be trained quickly number 2 wouldn't really matter, we could just do a grid search(or even particle swarm optimization. Or maybe Bayesian optimization. The amount of time to train is counted in days so better hope your first guess was good. I have posted a numpy implementa...
DANIEL SLATER'S BLOG: Mini-Pong and Half-Pong
http://www.danielslater.net/2016/05/mini-pong-and-half-pong.html
Monday, May 2, 2016. I'm going to be giving a talk/tutorial at PyDataLondon 2016. On Friday the 6th of may, if your in London that weekend I would recommend going, there are going to be lots of interesting talks, and if you do go please say hi. Possibly they are using other tricks not reported in the paper, or just lots of hyper parameter tuning, or there are still more bugs in my implementation(entirely possible, if anyone finds any please submit). Distance from building our future robot overlords, stil...
Xin-Yu Ou（欧新宇）
http://ouxinyu.github.io/Link.html
无监督学习和深度学习 Tutorial，由 Stanford Andrew Ng 团队领导完成，十分适合想要学习深度学习童鞋. 由 Stanford 教授 Andrew NG 领衔创办的教育平台，它与全世界最顶尖的大学和机构合作，提供任何人可学习的免费在线课程。 Discover the current state of the art in objects classification. Include MNIST, CIFAR-10, CIFAR-100, STL-10, SVHN, ILSVRC2012 task1. WikiCFP is a semantic wiki for Calls For Papers in science and technology fields. There are about 40,000 CFPs on WikiCFP. Over 100,000 researchers use WikiCFP each month. VALSE QQ群 364188996，VALSE-B QQ群 422075165. Caffe is a deep learning frame...
machine learning – Bcomposes
http://bcomposes.com/category/machine-learning
Computational linguistics, machine learning, programming, and random thoughts. Simple end-to-end TensorFlow examples. A walk-through with code for using TensorFlow on some simple simulated data sets. I’ve been reading papers about deep learning for several years now, but until recently hadn’t dug in and implemented any models using deep learning techniques for myself. To remedy this, I started experimenting with Deeplearning4J. A few weeks ago, but with limited success. I read more books. At the Universi...
R – Bcomposes
http://bcomposes.com/category/r
Computational linguistics, machine learning, programming, and random thoughts. Simple end-to-end TensorFlow examples. A walk-through with code for using TensorFlow on some simple simulated data sets. I’ve been reading papers about deep learning for several years now, but until recently hadn’t dug in and implemented any models using deep learning techniques for myself. To remedy this, I started experimenting with Deeplearning4J. A few weeks ago, but with limited success. I read more books. At the Universi...
July | 2015 | Bits and pieces
https://srippa.wordpress.com/2015/07
A collection of items that interest me. July 24, 2015. May 6, 2016. Getting started with Deep learning. Structures list of videos, tutorials, courses on AI, cognitive computing and deep learning. Another link to various AI related resources. Tutorials and best data scientists to follow (2015). List of best blogs to follow (2015). Deep learning tutorial from Stanford. Deep learning in a nutshell:. Nandos de Freitas: YouTube video series. Deep learning summer school 2015. ML class 10-701 (2015). List of Py...
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I. E. Colegio Agustina Ferro. Ocaña, Norte de Santander. Colombia. - I. E. Colegio Agustina Ferro - Ocaña, Norte de Santander, Colombia
Quién fue Agustina Ferro? Todas las fotografías de eventos y la vida escolar en la I. E. Colegio Agustina Ferro. La Institución Educativa Colegio Agustina Ferro prepara, de manera integral, jóvenes emprendedores, competentes y transformadores. Feria de la creatividad y el emprendimiento 2016. Publicado el 11 Noviembre 2016. Los docentes del área contable, organizadores del evento, manifestaron su satisfacción por el éxito de la feria y la acogida por parte de la comunidad educativa, al tiempo que agradec...
Blog de cOlah-fOr3v3r-x - </3 - Skyrock.com
Mot de passe :. J'ai oublié mon mot de passe. Bye Les Gens =). A: je suis si triste, je pleure. H: cOlah-fOr3v3r-x.ce pseudo ne lui corespond plus. /3. CØLAH Land *o* (75). Mise à jour :. CØLAH IS DEAD. CE Commentaire est magni. Abonne-toi à mon blog! CE Commentaire est magnifique, Hanna and Laura, lisez-le:. Les COLAH Isn't Dead . peut-etre maintenant, mais on reviendras en force ;). Je n'oublirais jamais tout les délirs qu'on a eu enssemble . Merci Morgane. 3 JE NAI JAMAIS IREN VOULU DE TOUT SA =@.
Blog de colah-nico - MiiKo Et C'eSt HiStOiRe - Skyrock.com
Mot de passe :. J'ai oublié mon mot de passe. MiiKo Et C'eSt HiStOiRe. Bien ,marrants ,et rigolo. Mise à jour :. Love Is Wicked (2007 Version) (Reggae). Abonne-toi à mon blog! MOI DAN MA CITY PLUTOT POPULAR! VS EN DITE KOOI. N'oublie pas que les propos injurieux, racistes, etc. sont interdits par les conditions générales d'utilisation de Skyrock et que tu peux être identifié par ton adresse internet (23.21.86.101) si quelqu'un porte plainte. Ou poster avec :. Posté le vendredi 20 février 2009 13:28.
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در من از دیوار حسرت عشق بالا می رود. آنچه شد یک عمر در دل حبس حالا می رود. تا که عشقت در دلم جوشید با من عقل گفت. عاقبت این چشمه روزی سوی دریا می رود. در من افسون تمنای تو پنهان جان گرفت. آنچه در عریانی چشم تو پیدا می رود. گرچه ما آسوده خاطر با شرر هم بستریم. دود از بالین ما در چشم دنیا می رود. کاروان عشق خواهد برد از ما عقل و هوش. بر نخواهد گشت این باری که از ما می رود. نوشته شده در سه شنبه بیست و سوم آذر ۱۳۸۹ساعت 21:19 توسط محمد حسین قمری. زندگی دلبخواهی است اينجا. می توانی برای خود باشی. خیال در سر ان...
Home - colah's blog
Neural Networks, Manifolds, and Topology. Deep Learning, NLP, and Representations. An Exploration of Dimensionality Reduction. Deep Learning and Human Beings. Groups and Group Convolutions. Fanfiction, Graphs, and PageRank. See the complete list of posts.
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