A sample network anomaly detection project Suppose we wanted to detect network anomalies with the understanding that an anomaly might point to hardware failure, application failure, or an intrusion. What our model will show us The RNN will train on a…
Open Data for Deep Learning Here you’ll find an organized list of interesting, high-quality datasets for machine learning research. We welcome your contributions for curating this list! You can find other lists of such datasets on Wikipedia, for exam…
HOME ABOUT CONTACT SUBSCRIBE VIA RSS DEEP LEARNING FOR ENTERPRISE Distributed Deep Learning, Part 1: An Introduction to Distributed Training of Neural Networks Oct 3, 2016 3:00:00 AM / by Alex Black and Vyacheslav Kokorin Tweet inShare27 This pos…
转自:http://www.jeremydjacksonphd.com/category/deep-learning/ Deep Learning Resources Posted on May 13, 2015 Videos Deep Learning and Neural Networks with Kevin Duh: course page NY Course by Yann LeCun: 2014 version, 2015 version NIPS 2015 Deep Learn…
What's the most effective way to get started with deep learning? 29 Answers Yoshua Bengio, My lab has been one of the three that started the deep learning approach, back in 2006, along with Hinton's... Answered Jan 20, 2016 Originally Ans…
Deep Learning Papers Reading Roadmap https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap.git Courses: Data Science: Deep Learning in Python https://www.udemy.com/data-science-deep-learning-in-python/#instructor Bay Area Deep Learning Sc…
Does Deep Learning Come from the Devil? Deep learning has revolutionized computer vision and natural language processing. Yet the mathematics explaining its success remains elusive. At the Yandex conference on machine learning prospects and applicati…
Game Theory Reveals the Future of Deep Learning Carlos E. Perez Deep Learning Patterns, Methodology and Strategy @ IntuitionMachine.com 译自:https://medium.com/intuitionmachine/game-theory-maps-the-future-of-deep-learning-21e193b0e33a#.2vjbrl5di 若你一直fo…
PROBLEM: OmniAnomaly multivariate time series anomaly detection + unsupervised 主体思想: input: multivariate time series to RNN ------> capture the normal patterns -----> reconstruct input data by the representations ------> use the reconstruction pr…
亚马逊链接 引言 (by Mehdi Roopaei & Paul Rad) 异态检测与情境感知 在数据分析领域,异态检测讲的是在一个数据集中,发现到其中不符合预期模式的物体,动作,行为或事件.异态检测在诸多领域都有被用到,比如生物识别防伪,医疗保健,信用卡诈骗检测,网络入侵检测,恶意程序检测,军事威胁监测.数据中的异态会由多种原因引发,这些原因有个共同点,就是数据科学家和网络分析者对它们很感兴趣(摊手).异态检测在不同的领域都已经有所研究和发展了,比如计算机科学,工程学,信息系统,以及网络安全…
Problem: unsupervised anomaly detection Model: VAE-reEncoder VAE with two encoders and one decoder. They use bidirectional bow-tie LSTM for each part. Why use bow-tie model: to remove noise to some extent when encoding.…
Problem: unsupervised anomaly detection for seasonal KPIs in web applications. Donut: an unsupervised anomaly detection algorithm based on VAE. Background: 有的time series data have seasonal patterns occurring at regular intervals. Data: KPI shapes: se…
Anomalies are data points that are few and different. As a result of these properties, we show that, anomalies are susceptible to a mechanism called isolation. This paper proposes a method called Isolation Forest (iForest) which detects anomalies pur…
1.结构图 Introduction Feature extraction, deformation handling, occlusion handling, and classification are four important components in pedestrian detection. Existing methods learn or design these components either individually or sequentially. The inte…
http://blog.csdn.net/pipisorry/article/details/44783647 机器学习Machine Learning - Andrew NG courses学习笔记 Anomaly Detection异常检測 Problem Motivation问题的动机 Anomaly detection example Applycation of anomaly detection Note:for Frauddetection: users behavior exam…
前言 论文“Reducing the Dimensionality of Data with Neural Networks”是深度学习鼻祖hinton于2006年发表于<SCIENCE >的论文,也是这篇论文揭开了深度学习的序幕. 笔记 摘要:高维数据可以通过一个多层神经网络把它编码成一个低维数据,从而重建这个高维数据,其中这个神经网络的中间层神经元数是较少的,可把这个神经网络叫做自动编码网络或自编码器(autoencoder).梯度下降法可用来微调这个自动编码器的权值,但是只有在初始化权值…
