deep learning with keras

The key of AI is machine learning, machine learning breakthrough is deep learning, artificial neural network.In 1956, in the Dartmouth Conference (Dartmouth conferences), computer scientists first introduced the term "AI", the AI was born, and in subsequent days AI became the "fantasy object" of the lab. Decades later,

Deep Reinforcement Learning Guide: http://mp.weixin.qq.com/s?__biz=MzI1NTE4NTUwOQ==mid=2650324914idx=1sn= 0baaf404b3d8132243d08b55310de210scene=2srcid=062732p5u33rrnikuedslvxnfrom=timeline Isappinstalled=0#wechat_redirect Detailed in-depth study, build DQN Guide (based on neon framework):https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==mid=2650716425idx=1sn= bf52c653b7cd054ce721ce5be928c623 "Multiagent coop

Recently, Google published in the Journal of the American Medical Council titled "Development and Validation of a deep learning algorithm for Detection of diabetic retinopathy in Reti NAL Fundus Photographs "is a deep learning algorithm that Google researchers have put forward to explain the signs of diabetic retinopat

First, it's up to the father of Ai, Turing. Turing once had a dream uninstall "computer and Intelligence" (1950) article, if one day, the computer can do, across the wall, you do not know the opposite and you communicate is a person or computer, then this computer has artificial intelligence. For the next half century, Ai has not developed much. Although the computer has the powerful memory and the data processing ability, but does not have the human cognition ability. For example, Wang, Meo

most important thing to know about OpenAI is to understand the frontiers of AI research.What is the research direction of Ai's frontier?OpenAI raised three points:-Training Generative Models-Algorithms for inferring algorithms from data-New approaches to reinforcement learningSo what do these three categories represent, respectively?Deep generative ModelsThe first type is oriented to the generation model, the main task is to generate new information,

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 deep

7 mins version:dqn for Flappy Bird Overview This project follows the description of the "Deep Q Learning algorithm described" Playing Atari with deep reinforcement L Earning [2] and shows that this learning algorithm can is further generalized to the notorious Flappy Bird. installation Dependencies: Python 2.7 or 3 Ten

Source: Michael Nielsen's "Neural Network and Deep leraning"This section translator: Hit Scir master Xu Zixiang (Https://github.com/endyul)Disclaimer: We will not periodically serialize the Chinese translation of the book, if you need to reprint please contact [email protected], without authorization shall not be reproduced."This article is reproduced from" hit SCIR "public number, reprint has obtained consent. " Using neural networks

This paper summarizes some contents from the 1th chapter of Neural Networks and deep learning. Catalogue Perceptual device S-type neurons The architecture of the neural network Using neural networks to recognize handwritten numbers Towards Deep learning Perceptron (perceptrons)1. Fundament

Recently studied a few days of deep learning of the MATLAB Toolbox code, found that the author gives the source of the comments is very poor, in order to facilitate everyone to read, the code has been commented, share with you.Before reading the MATLAB Toolbox code, we recommend that you read a few CNN two classic materials, the convolutional neural Network MATLAB Toolbox Code understanding is very helpful,

the first week after-school assignment is a 10-course choice question Note: The answer is from the first one and then the ABCD ... The answer has its own understanding, there are also from the online blog reference, only to learn.1. First questionI understand the answer: D.Reference answer: A. "AI is the new power", this is the topic of Wunda Teacher's speech on AI conference this year. Of course, the analogy is that AI, like electricity 100 years ago, is bringing great changes to our productiv

to be personal, but it's easy to look at SAS help. The PDV mechanism of SAS and the execution mechanism of macros must be understood. SAS has a great advantage, the standard of unification, as long as the learning to be able to swim throughout the system. R VS python: In contrast, R is statistically much stronger than Python because Statsmodel does not give force, and new statistical methods Python cannot keep pace. In the area of data mining, Pytho

Source: ICML Deep learning workshopgoogle DeepMind Innovation point: Building the first large-scale distributed architecture for depth-enhanced learningThe structure consists of four parts: Parallel action: Used to generate new behavior Parallel learner: Used to train from storage experience Distributed neural Networks: used to represent value function or policy Distributed experience S

As a deep learning platform developed by Baidu, paddjavasaddle is easy to learn, easy to use, and flexible and efficient, greatly reducing developers' R D thresholds. To help developers build a fast and Advanced path to deep learning, Baidu opened the "Deep

capabilities and work in areas where human experience is missing. In recent years, the use of intensive learning and training of the deep neural network has made rapid progress. These systems have surpassed the level of human players in video games, such as atari[6,7] and 3D virtual Games [8,9,10]. However, the most challenging areas of play in terms of human intelligence, such as Weiqi, are widely conside

/* author:cyh_24 *//* date:2014.10.2 *//* Email: [Email protected] *//* more:http://blog.csdn.net/cyh_24 */Recently, the focus of the study in the image of this piece of content, the recent game more, in order not to drag the hind legs too much, decided to study deeplearning, mainly in Theano the official course deep Learning tutorial for reference.This series of blog should be continuously updated, I hope

algorithm called Rmsprop can also be used to accelerate the mini-batch gradient decline, it is on the basis of MOMENTUAM modified, the formula as shown, DW into the square of the DW, in the fall when more divided by a radical. Can be understood as the vertical direction of the differential term is relatively large, so divided by a larger number, the horizontal direction of the differential term is relatively small, so divided by a relatively small number, so that can eliminate the downward swin

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

Deep learning veteran Yann LeCun detailed convolutional neural network The author of this article: Li Zun 2016-08-23 18:39 This article co-compiles: Blake, Ms Fenny Gao Lei Feng Net (public number: Lei Feng net) Note: convolutional Neural Networks (convolutional neural network) is a feedforward neural network, its artificial neurons can respond to a part of the coverage of the sur

Kevin Zakka ' s blogaboutnuts and bolts of applying deep learningSep 26, 2016This weekend is very hectic (catching up on courses and studying for a statistics quiz), but I managed-squeeze in some Time to watch the Bay area deep learning School livestream on YouTube. For those of your wondering what's is, Badls are a 2-day conference hosted at Stanford University,