deep learning framework comparison

Mark, let's study for a moment.Original address: http://www.csdn.net/article/2015-09-15/2825714Python1. Theano is a Python class library that uses array vectors to define and calculate mathematical expressions. It makes it easy to write deep learning algorithms in a python environment. On top of it, many classes of libraries have been built.1.Keras is a compact, highly modular neural network library that is

He admired the bronze teacher for a long time, and when he learned that he had written a book on learning methods, "The art of deep learning", he bought the first ebook I paid for in my life on the Amazon China website.This reading note is not exactly in accordance with the original book narrative sequence excerpt, but through my modification and collation.Readin

This article refers to http://blog.csdn.net/zdy0_2004/article/details/43896015 translation and the original file:///F:/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9% A0/recommending%20music%20on%20spotify%20with%20deep%20learning%20%e2%80%93%20sander%20dieleman.htmlThis article is a blog post by Dr. Sander Dieleman, Reservoir Lab Laboratory at the University of Ghent (Ghent University) in Belgium, where his research focuses on the classification of Music audio signals and the recommended hierarchical charac

Overview This demo is very suitable for beginners AI and deep learning students, from the most basic knowledge, as long as there is a little bit of advanced mathematics, statistics, matrix of relevant knowledge, I believe you can see clearly. The program is written without the use of any third-party deep Learning Libra

to the ROR framework, including the design method, the database operation of the active record mode, the design level is elegant, no redundant library, all the functions are purely framework, execution efficiency is good; database layer HasOne, Hasmany function is very powerful, more suitable for complex business processing, routing function, configuration function is good, automatic building scaffolding (

deep understanding of machine learning: Learning Notes from principles to algorithms-1th week 02 easy to get started Deep understanding of machine learning from principle to algorithmic learning notes-1th week 02 Easy to get star

elegant, no redundant library, all the functions are purely framework, execution efficiency is good; database layer HasOne, Hasmany function is very powerful, more suitable for complex business processing, routing function, configuration function is good, automatic building scaffolding (scaffold) is very powerful, suitable for medium-sized applications, basic implementation of MVC every layer, with automatic command line script function; 2. Document

line script function; 2. Document comparison of the whole, in the domestic promotion of comparative success, most of them know cakephp, learning costs Moderate Disadvantages: 1. The very serious problem with cakephp is that the model is understood as a database-level operation that severely affects operational capabilities beyond the database 2. CakePHP's cache function is slightly weak, the configuration

Distributed deep learning on MPP and HadoopDecember 17, 2014 | FEATURES | by Regunathan RadhakrishnanJoint work performed by Regunathan Radhakrishnan, Gautam Muralidhar, Ailey Crow, and Sarah Aerni of Pivotal's Data science Labs.Deep learning greatly improves upon manual design of features, allows companies to get more insights from data, and Shorte NS the time t

0. OriginalDeep learning algorithms with applications to Video Analytics for A Smart city:a Survey1. Target DetectionThe goal of target detection is to pinpoint the location of the target in the image. Many work with deep learning algorithms has been proposed. We review the following representative work:SZEGEDY[28] modified the

Based on metrics. Evaluate () can provide multiple metrics, _ my_metric_op custom, tr. contrib comes. Optimizer provides custom functions to define its own optimization function, including the Exponential decline learning rate. Tf. contrib. framework. get_or_create_global_step. Tf. train. exponential_decay () degrades the learning rate index to avoid gradient ex