deep learning with keras

How Yahoo implements large-scale distributed deep learning on Hadoop Clusters Over the past decade, Yahoo has invested a lot of energy in the construction and expansion of Apache Hadoop clusters. Currently, Yahoo has 19 Hadoop clusters, including more than 40 thousand servers and over Pb of storage. They developed large-scale machine learning algorithms on these

Original: http://blog.jobbole.com/87148/Editor's note "for an old question on Quora: What are the advantages of different classification algorithms?" Xavier Amatriain, a Netflix engineering director, recently gave a new answer, and in turn recommended the logic regression, SVM, decision tree integration and deep learning based on the principles of the Ames Razor, and talked about his different understanding

"Editor's note" for an old question on Quora: What are the advantages of different classification algorithms? Xavier Amatriain, a Netflix engineering director, recently gave a new answer, and in turn recommended the logic regression, SVM, decision tree integration and deep learning based on the principles of the Ames Razor, and talked about his different understandings. He does not recommend

http://m.blog.csdn.net/blog/wu010555688/24487301This article has compiled a number of online Daniel's blog, detailed explanation of CNN's basic structure and core ideas, welcome to exchange.[1] Deep Learning Introduction[2] Deep Learning training Process[3] Deep

IT168 commented on Google's Open source TensorFlow (GitHub) Earlier this week, a move that has had a huge impact in deep learning because Google has a strong talent pool in the field of AI research, And Google's own Gmail and search engines are using deep learning tools that are developed on their own.

Google Open source TensorFlow (GitHub) Earlier this week, a move that has a huge impact on deep learning because Google has a strong talent pool, and Google's own Gmail and search engines are using a self-developed deep learning tool.Undoubtedly, the TensorFlow from the Google arsenal is necessarily the star of the ope

Course Description: This is an introductory course on deep learning, and deep learning is mainly used for machine translation, image recognition, games, image generation and more. The course also has two very interesting practical projects: (1) Generate music based on RNN (2) Basic X-ray detection, GitHub address: Http

The Promise of deep learningby Yoshua BengioHumans has a long dreamed of creating machines that think. More than years before the first programmable computer is built, inventors wondered whether devices made of rods and Gears might become intelligent. And when Alan Turing, one of the pioneers of computing in the 1940s, set a goal for computer science, he described a test, Later dubbed the Turing Test, which measured a computer ' s performance against

1. Preface AI is a current hot topic, from the current Google's Alphago to smart cars, artificial intelligence has entered all aspects of our lives. Machine learning is a method of implementing artificial intelligence, which uses algorithms to analyze data, then learn from it, and finally make predictions and decisions about reality. Deep learning, however, is a

usually used only when there are a large number of annotated training data. In such cases, fine tuning can significantly improve the performance of the classifier. However, if there are a large number of unlabeled datasets (for unsupervised feature learning/pre-training), there are only relatively few annotated training sets, and the effect of fine tuning is very limited.The previously mentioned network is generally three layers, the following is a g

The 1th chapter introduces the course of deep learning, mainly introduces the application category of deep learning, the demand of talents and the main algorithms. This paper introduces the course chapters, the course arrangement, the applicable crowd, the prerequisites and the degree to be achieved after the completio

Yun-June Guide : This article introduces deep learning and bongard problems, and how to use deep learning to better solve bongard problems. The Bongard problem was proposed by Soviet computer scientist Mikhail Bongard. Since the 1960s, he has been working on pattern recognition, and has designed 100 such puzzles to ma

Deep learning and the Triumph of empiricismby Zachary Chase Lipton, July 2015Deep Learning are now the standard-bearer for many tasks in supervised machine learning. It could also is argued that deep learning have yielded the most

used in the Googlenet V2.4, Inception V4 structure, it combines the residual neural network resnet.Reference Link: http://blog.csdn.net/stdcoutzyx/article/details/51052847Http://blog.csdn.net/shuzfan/article/details/50738394#googlenet-inception-v2Seven, residual neural network--resnet(i) overviewThe depth of the deep learning Network has a great impact on the final classification and recognition effect, so

Editor's note: Quora on the question: self-study machine learning technology, what advice do you have? (What is your recommendations for self-studying machine learning), Yann LeCun The answer under the question. This article by Lei Feng Net (public number: Lei Feng net) according to LeCun's reply collation, the original link: http://www.leiphone.com/news/201611/cWf2B23wdy6XLa21.htmlThere are a lot of materi

Turn from deep learning public numberThis article is from: InfoQHttp://www.infoq.com/cn/news/2016/01/evaluation-comparison-deep-learnArtificial intelligence is undoubtedly the forefront of the computer world, and deep learning is undoubtedly the focus of artificial intellige

Article source:http://www.infoq.com/cn/news/2016/01/evaluation-comparison-deep-learn?utm_campaign=infoq_content Evaluation and comparison of deep learning frameworkArtificial intelligence is undoubtedly the forefront of the computer world, and deep learning is undoubtedly th

Shang Xu June, human body behavior recognition based on Deep learning J Wuhan University Journal 2016414492-497 Introduction Behavior Recognition Overall process Foreground extraction Behavior Recognition Process Experimental analysis Computer Engineering and application of pedestrian detection based on deep convolutio

This article is the Adam method for the Deep Learning series article. The main reference deep Learning book. Complete list of optimized articles: Optimal method of Deep Learning SGD Deep