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[Deep Learning] Implementing a game-based AI, starting with wuziqi (2) Well, today we are going to start playing wuziqi and start talking to our friends about AI. Last night we had implemented a logical part of wuziqi. In fact, there is a rule in which AI can be started, but it is not intuitive enough, we recommend that you first develop the UI of wuziqi. So today we are engaged in the UI. The logic part
feature algorithms, our goal is usually to isolate the variables that explain the observed data.Deep learning allows a computer to construct complex concepts through simpler concepts. (The examples in the comparison book can be understood clearly)The idea of learning the correct representation of data is a point of view for explaining
Document directory 1.1 how to restrict the use of the Polman machine (RBM) 1.2 restricted Polman machine (RBM) Energy Model 1.3 from energy model to probability 1.4 Maximum Likelihood 1.5 Sampling Method Used 1.6 introduction to Markov Monte Carlo References RBM for deep learning Reading Notes Statement: 1) I saw a statement from other blogs such as @ zouxy09, and the old man copied it. 2) This blo
Reprinted from Alchemy Laboratory: https://zhuanlan.zhihu.com/p/24720954 I have previously written an article about deep learning training skills, which includes some of the assistant experience: Deep learning training experience. However, as a result of the general deep
Recently in the NetEase Cloud classroom learning "depth study" micro-professional, the class after the programming work record down. Deep Learning – Wunda The logical regression written in Python before comparison deeplearning operation Logistic regression with a neural network mindset Welcome to your (required) progra
When does the deep learning model in NLP need a tree structure?Some time ago read Jiwei Li et al and others [1] in EMNLP2015 published the paper "When is the Tree structures necessary for the deep learning of representations?", This paper mainly compares the recursive neural network based on tree structure (Recursive n
) In 2013, Nal Kalchbrenner and Phil Blunsom presented a new end-to-end encoder-decoder architecture for machine translation. In 2014, Sutskever developed a method called sequence-to-sequence (seq2seq) learning, and Google used this model to give a concrete implementation method in the tutorial of its deep learning framework
Deep Learning (ii) sparse filtering sparse Filtering Zouxy09@qq.com Http://blog.csdn.net/zouxy09 I have read some papers at ordinary times, but I always feel that I will slowly forget it after reading it. I did not seem to have read it again one day. So I want to sum up some useful knowledge points in my thesis. On the one hand, my understanding will be deeper, and on the other hand, it will facilitate fut
CNN began in the 90 's lenet, the early 21st century silent 10 years, until 12 Alexnet began again the second spring, from the ZF net to Vgg,googlenet to ResNet and the recent densenet, the network is more and more deep, architecture more and more complex, The method of vanishing gradient disappears in reverse propagation is also becoming more and more ingenious. LeNet AlexNet Zf Vgg Googlenet ResNet Densenet
Write in front:has not tidied up the habit, causes many things to be forgotten, misses. Take this opportunity to develop a habit.Make a collation of the existing things, record, to explore and share new things.So the main content of the blog for I have done, the study of the collation of records and new algorithms, network framework of learning. It's basically about dee
parallel. However, partial parallelism can be achieved by self-sampling SGBT.8, GBDTAdvantages: 1, can flexibly deal with various types of data, including continuous and discrete values, processing classification and regression problems, 2, in the relatively few parameters of the time, the forecast preparation rate can also be relatively high. This is relative to the SVM, 3, can be used to filter features.4, using some robust loss function, the robustness of outliers is very strong. such as Hub
Unsupervised learning Using generative adversarial Training and Clustering–authors:vittal Premachandran, Alan L. Yuille An information-theoretic Framework for Fast and robust unsupervised learning via neural Population Infomax–authors:wenta o Huang, Kechen Zhang Unsupervised Cross-domain Image generation–authors:yaniv Taigman, Adam Polyak, Lior Wolf Unsuper
JS doing deep learning, accidental discovery and introductionRecently I first dabbled with node. js, and used it to develop a graduation design Web module, and then through the call System command in node execution Python file way to achieve deep learning function module docking, Python code intervention, make JS code
[Tools] Small test and learning project configuration framework and configuration framework Download: Personal_Study_Assistant.zip Background In reality, we may often have to be unsure about Some APIs or small core code, so we write some small test code, such as regular expression testing. After a long time, all these small projects are scattered, and searching
dramatically. The most important thing is that there is no way to use the framework of deep learning.3. Use the Python process to run a trained model in deep learning and invoke the services provided by the Python process in a Java application. This method I think is the be
Computational Network Toolkit (CNTK) is a Microsoft-produced open-Source Deep learning ToolkitUsing CNTK to engage in deep learning (a) Getting StartedComputational Network Toolkit (CNTK) is a Microsoft-produced open-source deep learning
1. Structure diagramIntroductionFeature extraction, deformation handling, occlusion handling, and classification is four important components in Pedestri An detection. Existing methods Learn or design these components either individually or sequentially. The interaction among these are not yet well explored. This paper proposes, they should be jointly learned in order to maximize their strengths through cooperation. We formulate these four to a joint deep
Deep learning articles and code collections for text categorizationOriginal: franklearningmachine Machine Learning blog 4 days ago [1] convolutional neural Networks for sentence classificationYoon KimNew York UniversityEMNLP 2014http://www.aclweb.org/anthology/D14-1181This article mainly uses CNN to classify sentences based on pre-trained word vectors. The auth
Preface: Recently, I intend to learn some theoretical knowledge of deep learing in a slightly systematic way, and intend to use Andrew Ng's Web tutorial Ufldl Tutorial, which is said to be easy to read and not too long. But before this, or review the basic knowledge of machine learning, see Web page: http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning. The content is actually ver
First spit groove, deep learning development speed is really fast, deep learning framework is gradually iterative, it is really hard for me to engage in deep learning programmer. I bega
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