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#Vote Weka - Bird of the Year 2017
 
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The New Zealand Weka - feisty, curious, flightless - and vulnerable. Please show you care, vote Weka for Bird of the Year at www.birdoftheyear.org.nz 9-23 October 2017
Views: 162 OnceUponAnIsland
Data Mining with Weka (1.1: Introduction)
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 1: Introduction http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 120182 WekaMOOC
WEKA bird dance
 
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WEKA dancing kiwi bird
Views: 1179 FarionMian
What is a Weka?
 
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A Weka is flightless bird, unique to New Zealand. It is also known for its cheeky, feisty personality. We are Island Keepers in the Hauraki Gulf of New Zealand and share the island with about 100 endangered North Island Weka. Our story is Once Upon An Island. More at www.facebook.com/onceonanisland And www.OnceUponAnIsland
Views: 1437 OnceUponAnIsland
Data Mining with Weka (1.2: Exploring the Explorer)
 
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Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 2: Exploring the Explorer http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 87968 WekaMOOC
How I Prepare Dataset For SVM Classifier
 
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English/Chinese subtitles are available for this video. 有中文字幕描述! Hi, all. As I am working on bird detection. I need to prepare dataset for training the SVM classifier. Here is how I did it. I use a small dataset(around 200 image), and trained the SVM with that one, then, I used the trained SVM as a gauge to measure how good a candidate new sample would be. As you can see from the video, the software tool will display the value of the distance the new image would be from the support vector. Any comment is appreciated. You can download version of the tool: http://www.phyxs.com/image-cropper-for-computer-vision
Views: 19829 PhyXs Vision
Advanced Data Mining with Weka (2.2: Weka’s MOA package)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 2: Weka’s MOA package http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/4vZhuc https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 2789 WekaMOOC
Weka Vs. Camera (Another Flightless New Zealand Bird)
 
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A Weka (Gallirallus australis) is a flightless New Zealand bird. This bird is foraging for food until someone places a video camera in front of him. Filmed on Panasonic HDC-HS80 and Panasonic TZ-30 Weka Attack
WEKA - Birliktelik Analizi
 
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Weka, Weka Analiz, WEKA - Birliktelik Analizi TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS https://www.kodkolik.net/ Weka, makine öğrenimi amacıyla Waikato Üniversitesinde geliştirilmiş ve "Waikato Environment for Knowledge Analysis" kelimelerinin baş harflerinden oluşmuş yazılımın ismidir. Günümüzde yaygın kullanımı olan çoğu makine öğrenimi algoritmalarını ve metotlarını içermektedir. Java dilinde geliştirilmiş olması ve kütüphanelerinin .jar dosyaları halinde geliyor olması sayesinde, Java dilinde yazılan projelere kolayce entegre edilebilmesi kullanımını daha da yaygınlaştırmıştır Yazılım, GNU Genel Kamu Lisansı ile dağıtılmaktadır. Weka, tamamen modüler bir tasarıma sahip olup, içerdiği özelliklerle veri kümeleri üzerinde görselleştirme, veri analizi, iş zekası uygulamaları, veri madenciliği gibi işlemler yapabilmektedir. Weka yazılımı, kendisine özgü olarak bir .arff uzantısı desteği ile gelmektedir. Ancak Weka yazılımının içerisinde CSV dosyalarını da ARFF formatına çevirmeye yarayan araçlar mevcuttur. Temel olarak aşağıdaki 3 Veri Madenciliği işlemi Weka ile yapılabilir: Sınıflandırma (Classification) Bölütleme (Clustering) İlişkilendirme (Association) Ayrıca yukarıdaki işlemlere ilave olarak, veri kümeleri üzerinde ön ve son işlemler yapılabilir Veri Ön işleme (Data Pre-Processing) Görselleme (Visualization) Son olarak Weka Kütüphanesi'nde veri kümelerini içeren dosyalar üzerinde çalışan çok sayıda hazır fonksiyon bulunmaktadır. Machine Learning Group at the University of Waikato Project Software Book Publications People Related Weka 3: Data Mining Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data!
More Data Mining with Weka (5.2: Multilayer Perceptrons)
 
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More Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 2: Multilayer Perceptrons http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/rDuMqu https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 29173 WekaMOOC
Advanced Data Mining with Weka (1.1: Introduction)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 1: Introduction http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/JyCK84 https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 6794 WekaMOOC
Excel - Weka İlişkisi
 
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Excel, Excel - Weka, Excel Weka İlişkisi, Excel Weka Eğitim Seti, Excel Weka Eğitim Serisi TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS http://kodkolik.net/ Machine Learning Group at the University of Waikato Project Software Book Publications People Related Weka 3: Data Mining Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data!
shortest distance between two sets of coordinates
 
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Calculation of shortest path (minimum Euclidean distance) between two sets of coordinates at http://imagejs.org/shortdistance.html. This little tool was developed to help Pathologists measuring distributions of distances between different components in a tissue slide.
Views: 5716 Jonas Almeida
Data MiningLabor Dataset
 
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This video is about labor dataset being solved by using WEKA Toll. Its for the classification of their data to be more manageable. Hope all of you can enjoy watching this video.
Views: 97 nurul atiqah
C# Machine Learning 01. Multivariate Linear Regression (Part 9)
 
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Blog: http://www.csharpexperiments.blogspot.in Google+: https://plus.google.com/u/0/+SandeepMS/posts
Views: 1381 C# Experiments
Data Mining with Weka: Trailer
 
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Trailer for the "Data Mining with Weka" MOOC (Massive Open Online Course) from the University of Waikato, New Zealand. http://weka.waikato.ac.nz/ https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Slides (PDF): https://docs.google.com/file/d/0B-f7ZbfsS9-xY2RlZGtpNVRjaUk/edit?usp=sharing Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 129085 WekaMOOC
Automagical Automation Secrets of The Superaffiliates | AWeurope 2016
 
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Automagical Automation Secrets of The Superaffiliates In 2016, superaffiliates are killing the competition with automation. And the competition's YOU. Learn how you can use the same tools to crush your campaigns - before someone else crushes you. Speech by Hugh Hancock Affiliate Expert & Founder, Machinima --- Website: https://affiliateworldconferences.com Facebook: https://www.facebook.com/affiliateworldconferences Twitter: https://twitter.com/AWConferences Instagram: https://www.instagram.com/AWConferences #AWeurope
Demo: Weka
 
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Let’s Write a Decision Tree Classifier from Scratch - Machine Learning Recipes #8
 
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Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well. You can find the code from this video here: https://goo.gl/UdZoNr https://goo.gl/ZpWYzt Books! Hands-On Machine Learning with Scikit-Learn and TensorFlow https://goo.gl/kM0anQ Follow Josh on Twitter: https://twitter.com/random_forests Check out more Machine Learning Recipes here: https://goo.gl/KewA03 Subscribe to the Google Developers channel: http://goo.gl/mQyv5L
Views: 168055 Google Developers
WilmaScope InfoVizCitationNetVisualization
 
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This was our entry for the Infovis 2004 competition, which won 1st place in the student category. The task was to visualize the Infovis conference's citation history. More info: http://hcil.cs.umd.edu/localphp/hcil/vast/archive/task.php?ts_id=138 More info about our entry, which was produced using the WilmaScope 3D graphviz software (http://wilma.sf.net) is available here: http://www.cs.umd.edu/hcil/InfovisRepository/contest-2004/1/unzip/index.html
Views: 336 Tim Dwyer
Tubes - Educational Data Mining
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/join -- Create animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
WEKA
 
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Views: 99 Christina Georgiou
Cross-Validation for Choosing a Solution in Multi-Objective Fuzzy Classifier Design
 
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Repeated Double Cross-Validation for Choosing a Single Solution in Evolutionary Multi-Objective Fuzzy Classifier Design. Full text available on ScienceDirect: http://dx.doi.org/10.1016/j.knosys.2013.09.023
Views: 302 Elsevier Journals
Veri Madenciliği(Excel -  Karışık Örnekler)
 
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Veri Madenciliği, Veri Madenciliği Dersleri, Veri Madenciliği Eğitim Seti, Veri Madenciliği Dersleri Serisi, Veri Madenciliği(Excel - Karışık Örnekler) TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS http://kodkolik.net/ Machine Learning Group at the University of Waikato Project Software Book Publications People Related Weka 3: Data Mining Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data!
Artificial Neural Network Tutorial | Deep Learning With Neural Networks | Edureka
 
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( TensorFlow Training - https://www.edureka.co/ai-deep-learning-with-tensorflow ) This Edureka "Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail. Below are the topics covered in this tutorial: 1. Why Neural Networks? 2. Motivation Behind Neural Networks 3. What is Neural Network? 4. Single Layer Percpetron 5. Multi Layer Perceptron 6. Use-Case 7. Applications of Neural Networks Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world. Please write back to us at [email protected] or call us at +91 88808 62004 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 57083 edureka!
Cluster-Versionทดลอง
 
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made with ezvid, free download at http://ezvid.com
Views: 116 Chawannut Prommin
The Live Wire - Knowledge Discovery in Databases
 
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Dr. Pamela Thompson, Adjunct faculty member, and Lavanya Loganarayanan, recent graduate, were the guests on the August 20 edition of “The Live Wire,” Inside UNC Charlotte’s streaming webcast. They discussed the course “Knowledge Discovery in Databases”, which is part of UNC Charlotte’s Data Science Initiative, and how UNC Charlotte students have analyzed diverse data sets related to sharks and have discovered that certain patterns emerge.
kNN Machine Learning Algorithm - Excel
 
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kNN, k Nearest Neighbors Machine Learning Algorithm tutorial. Follow this link for an entire Intro course on Machine Learning using R, did I mention it's FREE: https://www.youtube.com/playlist?list=PLjPbBibKHH18I0mDb_H4uP3egypHIsvMn Also, be sure to check out my channel for over 300 tutorials on Excel, R, Statistics, basic Math, and more.
Views: 60860 Jalayer Academy
Open Data Project
 
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Open Data Project for visualising, discussing and rating datasets from data.gov.in for the OpenAppsChallenge
Views: 304 webnotestech
Natural Language Generation (Introduction)
 
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For more AI and Computer Science videos visit http://www.lemiffe.com/learning
Views: 7665 lemiffelearning
Using Python for Sarcasm Detection in Speech
 
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Rachel Rakov http://www.pyvideo.org/video/3773/using-python-for-sarcasm-detection-in-speech https://pygotham.org/2015/talks/152/using-python-for-sarcasm-detection-in-speech In this talk, I discuss my work using Python to create a system for sarcasm detection in speech. My goal in this task is to determine whether human intonation alone can be modeled to predict sarcastic speech. I first extracted speech samples from the titular character of MTV’s late ‘90s hit TV show “Daria”. Using crowdsourcing techniques to get the speech labeled for sarcasm, I created a corpus of speech that is annotated for sarcasm and sincerity. I used several Python toolkits to extract a number of acoustic features from this speech that are indicative of sarcasm. The first tool I used was Snack Sound Toolkit, a library for Python that does basic sound handling and analysis. I used tools in Snack to extract a baseline of basic acoustic features that have been found to be helpful in human sarcasm identification. I then used NumPy, SciPy, and NLTK to model prosodic contours, and applied these contours to the task of automatic sarcasm detection. This approach applies sequential modeling to representations of pitch and intensity curves obtained via k-means clustering. Using machine learning (specifically Weka’s SimpleLogistic (LogitBoost) classifier), this system is able to predict sarcasm with 81.57% accuracy.
Views: 3026 Next Day Video
Introduction of Neural Network Theory - Part IV
 
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Tutorial sobre Mineração de Dados (Data Mining) utilizando o software WEKA. Acesso http://mineracaodedados.wordpress.com o maior site sobre Data Mining do Brasil.
Views: 121 Flávio Clésio
Configuration de Pentaho Design Studio
 
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Configuration et installation de Pentaho Design Studio
Views: 3697 Sylvain Decloix
Introduction of Neural Network Theory - Exercises
 
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Tutorial sobre Mineração de Dados (Data Mining) utilizando o software WEKA. Acesso http://mineracaodedados.wordpress.com o maior site sobre Data Mining do Brasil.
Views: 474 Flávio Clésio
machine learning training validation testing
 
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goo.gl/bWr3z9 http://www.bigdatatraining.in/ WebSite: http://www.bigdatatraining.in Mail: [email protected] Call: +91 9789968765 044 - 42645495 Call –: +91 97899 68765 / +91 9962774619 / 044 – 42645495 Weekdays / Fast Track / Weekends / Corporate Training modes available Our Trainings Also available across India in Bangalore, Pune, Hyderabad, Mumbai, Kolkata, Ahmedabad, Delhi, Gurgon, Noida, Kochin, Tirvandram, Goa, Vizag, Mysore,Coimbatore, Madurai, Trichy, Guwahati & Chennai On-Demand Fast track Trainings globally available also at Singapore, Dubai, Malaysia, London, San Jose, Beijing, Shenzhen, Shanghai, Ho Chi Minh City, Boston, Wuhan, San Francisco, Chongqing
Views: 87 electra8267
Hands-On with the 10TB LaCie d2 Professional External Hard Drive!
 
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As a content creator, there is never enough storage space to go around but the LaCie d2 Professional aims to solve this problem with its massive 10TB of storage and fast transfer speeds! Check out our quick hands-on with this massive hard drive. LaCie d2 Professional - https://amzn.to/2Prb7jl
Views: 3920 MacRumors
Sparse and large-scale learning with heterogeneous data
 
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Google Tech Talks September 5, 2006 Gert Lanckriet is assistant professor in the Electrical and Computer Engineering Department at the University of California, San Diego. He conducts research on machine learning, applied statistics and convex optimization with applications in computational biology, finance, music and vision. ABSTRACT An important challenge for the field of machine learning is to deal with the increasing amount of data that is available for learning and to leverage the (also increasing) diversity of information sources, describing these data. Beyond classical vectorial data formats, data in the format of graphs, trees, strings and beyond have become widely available for data mining, e.g., the linked structure of the world wide web, text, images and sounds on web pages, protein interaction networks, phylogenetic trees, etc. Moreover, for interpretability and economical reasons, decision rules that rely on a small subset of the information sources and/or a small subset of the features describing the data are highly desired: sparse learning algorithms are a must. This talk will outline two recent approaches that address sparse, large-scale learning with heterogeneous data, and show some applications. Google engEDU Speaker: Gert Lanckriet
Views: 806 GoogleTalksArchive
Wendy Kopp: Learning Curves Never End
 
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CEO and Founder Wendy Kopp discusses Teach For America's challenge to face major organizational learning curves, in its early years. Kopp describes how this process continues, as the organization works to better answer questions around issues of recruitment, training, professional development, management, and financing. View more clips and share your comments at http://ecorner.stanford.edu/authorMaterialInfo.html?mid=2600
Views: 1090 Stanford eCorner
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
 
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While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ActiVis, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ActiVis has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ActiVis may work with different models. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models. Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, Duen Horng (Polo) Chau. Published in IEEE Transactions on Visualization and Computer Graphics, Vol. 24, No. 1, January 2018. Presented at IEEE Conference on Visual Analytics Science and Technology (VAST), Phoenix, Arizona, USA, October 2017.
ARTigo Scatterplot Visualization - Art History Data Science
 
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Visualizing 16384 art works, based on crowd sourced tagging data from http://artigo.org/ One can easily spot clusters such as: color portraits, black and white portraits, landscapes, modern art, architecture. Visualization done using ELKI http://elki.dbs.ifi.lmu.de/
Views: 568 Erich Schubert
Evaluation 9: when recall/precision is misleading
 
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Recall / precision pairs should not be used for comparing two search algorithms, because search engines output rankings, not sets. Different recall/precision pairs can be observed at different points in the ranking, so any comparison is meaningless unless we pre-specify a thresholding strategy.
Views: 3459 Victor Lavrenko
On-Demand Information Extraction
 
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Google Tech Talks August 23, 2007 ABSTRACT At present, adapting an Information Extraction system to new topics is an expensive and slow process, requiring some knowledge engineering for each new topic. We propose a new paradigm of Information Extraction which operates 'on demand' in response to a user's query. On-demand Information Extraction (ODIE) aims to completely eliminate the customization effort. Given a user's query, the system will automatically create patterns to extract salient relations in the text of the topic, and build tables from the extracted information using paraphrase discovery technology. It relies on recent advances in pattern discovery, paraphrase discovery, and extended named entity tagging. I will show you a demo system, which produces a table in less than a minute for any given query. Speaker: Satoshi Sekine Google engEDU Speaker: Satoshi Sekine
Views: 225 GoogleTalksArchive
2014-10-06 Ray Mooney, Generating Natural-Language Video Descriptions Using Text-Mined Knowledge
 
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Talk @ UW NLP Seminar, 10/06/2014 Title: Generating Natural-Language Video Descriptions Using Text-Mined Knowledge Speaker: Ray Mooney (The University of Texas at Austin) Abstract: We present a method for automatically generating English sentences describing short videos by combining techniques from computer vision and natural-language processing. We first use state-of-the-art visual object , scene, and activity recognizers to determine a potential set of entities, scenes, and actions in the video. We then use statistics mined from large parsed corpora of English to determine the most probable subject-verb-object-scene tuple, which is then used to generate a descriptive English sentence. Experimental results on a corpus of YouTube videos demonstrate the capabilities of the system, including "zero-shot" recognition of activities never seen during training. Bio: Raymond J. Mooney is a Professor in the Department of Computer Science at the University of Texas at Austin. He received his Ph.D. in 1988 from the University of Illinois at Urbana/Champaign. He is an author of over 150 published research papers, primarily in the areas of machine learning and natural language processing. He was the President of the International Machine Learning Society from 2008-2011, program co-chair for AAAI 2006, general chair for HLT-EMNLP 2005, and co-chair for ICML 1990. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery, and the recipient of best paper awards from AAAI-96, KDD-04, ICML-05 and ACL-07.
Views: 474 Yoav Artzi
Humans Need Not Apply
 
15:01
Discuss this video: http://www.reddit.com/r/CGPGrey/comments/2dfh5v/humans_need_not_apply/ http://www.CGPGrey.com/ https://twitter.com/cgpgrey ## Robots, Etc: Terex Port automation: http://www.terex.com/port-solutions/en/products/new-equipment/automated-guided-vehicles/lift-agv/index.htm Command | Cat MieStar System.: http://www.catminestarsystem.com/capability_sets/command Bosch Automotive Technology: http://www.bosch-automotivetechnology.com/en/de/specials/specials_for_more_driving_safety/automated_driving/automated_driving.html Atlas Update: https://www.youtube.com/watch?v=SD6Okylclb8&list=UU7vVhkEfw4nOGp8TyDk7RcQ Kiva Systems: http://www.kivasystems.com PhantomX running Phoenix code: https://www.youtube.com/watch?v=rAeQn5QnyXo iRobot, Do You: https://www.youtube.com/watch?v=da-5Uw8GBks&list=UUB6E-44uKOyRW9hX378XEyg New pharmacy robot at QEHB: https://www.youtube.com/watch?v=_Ql1ZHSkUPk Briggo Coffee Experience: http://vimeo.com/77993254 John Deere Autosteer ITEC Pro 2010. In use while cultivating: https://www.youtube.com/watch?v=VAPfImWdkDw&t=19s The Duel: Timo Boll vs. KUKA Robot: https://www.youtube.com/watch?v=tIIJME8-au8 Baxter with the Power of Intera 3: https://www.youtube.com/watch?v=DKR_pje7X2A&list=UUpSQ-euTEYaq5VtmEWukyiQ Baxter Research Robot SDK 1.0: https://www.youtube.com/watch?v=wgQLzin4I9M&list=UUpSQ-euTEYaq5VtmEWukyiQ&index=11 Baxter the Bartender: https://www.youtube.com/watch?v=AeTs9tLsUmc&list=UUpSQ-euTEYaq5VtmEWukyiQ Online Cash Registers Touch-Screen EPOS System Demonstration: https://www.youtube.com/watch?v=3yA22B0rC4o Self-Service Check in: https://www.youtube.com/watch?v=OafuIBDzxxU Robot to play Flappy Bird: https://www.youtube.com/watch?v=kHkMaWZFePI e-david from University of Konstanz, Germany: https://vimeo.com/68859229 Sedasys: http://www.sedasys.com/ Empty Car Convoy: http://www.youtube.com/watch?v=EPTIXldrq3Q Clever robots for crops: http://www.crops-robots.eu/index.php?option=com_content&view=article&id=62&Itemid=61 Autonomously folding a pile of 5 previously-unseen towels: https://www.youtube.com/watch?v=gy5g33S0Gzo#t=94 LS3 Follow Tight: https://www.youtube.com/watch?v=hNUeSUXOc-w Robotic Handling material: https://www.youtube.com/watch?v=pT3XoqJ7lIY Caterpillar automation project: http://www.catminestarsystem.com/articles/autonomous-haulage-improves-mine-site-safety Universal Robots has reinvented industrial robotics: https://www.youtube.com/watch?v=UQj-1yZFEZI Introducing WildCat: https://www.youtube.com/watch?v=wE3fmFTtP9g The Human Brain Project - Video Overview: https://www.youtube.com/watch?v=JqMpGrM5ECo This Robot Is Changing How We Cure Diseases: https://www.youtube.com/watch?v=ra0e97Wiqds Jeopardy! - Watson Game 2: https://www.youtube.com/watch?v=kDA-7O1q4oo What Will You Do With Watson?: https://www.youtube.com/watch?v=Y_cqBP08yuA ## Other Credits Mandelbrot set: https://www.youtube.com/watch?v=NGMRB4O922I&list=UUoxcjq-8xIDTYp3uz647V5A Moore's law graph: http://en.wikipedia.org/wiki/File:PPTMooresLawai.jpg Apple II 1977: https://www.youtube.com/watch?v=CxJwy8NsXFs Beer Robot Fail m2803: https://www.youtube.com/watch?v=N4Lb_3_NMjE All Wales Ambulance Promotional Video: https://www.youtube.com/watch?v=658aiRoVp6s Clyde Robinson: https://www.flickr.com/photos/crobj/4312159033/in/photostream/ Time lapse Painting - Monster Spa: https://www.youtube.com/watch?v=ED14i8qLxr4
Views: 10805987 CGP Grey
twitterati - jan [wk2] - 'using the twitter firehose to scan for social updates'
 
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a question this week led to suggests of how to find data about who are the most active charities out there and how to use an element of an api to get some realtime data back to make a decision from. ideas for using the streaming api of twitter (or just save yourself time and use datasift) to grab keywords regarding charities so you know which popular ones to support from the get go. this could be really useful process actually for building services that actually add additional layers of sentiment onto conversations if used correctly and spammy as heck if used badly. ---------------- facebook ---------------- https://www.facebook.com/cellar54 ------------------ twitter ------------------ http://twitter.com/philcampbell ------------------ tumblr ------------------ http://dasider.tumblr.com -------------- web tv studio ------------  http://cellar54.tv ------------- social objects ------------ http://meetdotdot.com http://meetcellbee.com ----------- hire my services ---------- http://fiverr.com/philcampbell http://j.mp/peopleperhour ---------- help me, help you ----------- donate : http://j.mp/digitalbunker wishlist : http://cellar54.tv/bartering load fiverr : http://j.mp/loadfiverr ----------   youtube shows   ----------- webnative -- http://j.mp/webnativeshow twitterati -- http://j.mp/twitteratishow pcmupdate -- http://j.mp/pcmupdate crowdworking -- http://j.mp/crowdworking sixbysix -- http://j.mp/sixbysixshow vlog 2013 -- http://j.mp/vlog2013 screencasts -- http://j.mp/thescreencast --------------- i’m using ---------------- - apogee mic 96k professional microphone (£199) - http://amzn.to/25nGQbt - logitech c920 web camera (£50) - http://amzn.to/25nPOFE i love and i want (for bella, videodirect and me!) - amazon fire tv game controller (£40) - http://amzn.to/25nJr5g (remote game playing) - amazon fire tv 4k (£80) - http://amzn.to/1TCV2I2 (static for videodirect/ella) - mis gs60 6qe ghost pro 4k - http://amzn.to/25nJIFs (need for mobile gaming!) - nintendo handheld console 3ds XL (£170) - http://amzn.to/25nKkuF (she lost last one!) - pokemon alpha sapphire (£40) - http://amzn.to/25nKfXL (new pokemon game!) - panasonic dmc-g7 camera (£500) - http://amzn.to/1TCXQoC (4k camera for nomad pics) - canon powershot g7x mark II (£620) - http://amzn.to/1TCYT7W (daily vlogging camera 60fps) - canon xa xc10 full hd (£800-£1600) - http://amzn.to/1TCYCSo (4k static shots for nomad.video) - lexar professional 64gb 3400x (£160) - http://amzn.to/1TD8snw (card for the camera above) - samsung galaxy s7 32gb (£465) - http://amzn.to/1TD2Bi1 (that android life) stuff you should check out - anker powercore 1000 portable charger (£16) - http://amzn.to/25nJAWg - anker powercore 20100 (£24) - http://amzn.to/1TCWrhR - aukey bluetooth sport headphones (£13) - http://amzn.to/1TCYSRm (sound awesome too!) - wakawaka base 5 (£99) - http://amzn.to/1XVtahS (great solar base for digital nomads) things i’m getting soon and will review - vanguard veo am-264tr (£80) - http://amzn.to/25nJNc5 (for vlogging/filming) - apple iPhone SE 64gb (£465) - http://amzn.to/25nPs1L (4k, up to date, speedy, content making) - uhuru rechargeable mouse, noiseless/silent click (£13) - http://amzn.to/1ZOyLG8 (course making) - gopro hero session camera (£159) - http://amzn.to/1TD9qQv (time-lapse, b-roll) - wakawaka base 10 (£140) - http://amzn.to/1XVsDga (solar charging on the road)
Views: 83 Phil Campbell
Big Data Course Clustering - Heuristics. Spring 2014 - Unit 20 Lesson 6. MOOC - Unit 16 Lesson 6
 
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Lesson Overview: Some remarks are given on heuristics; why are they so important why getting exact answers is often not so important? Enroll in this course at https://bigdatacourse.appspot.com/ and download course material, see information on badges and more. It's all free and only takes you a few seconds.
2011 Frontiers of Engineering: Advancing Natural Language Understanding
 
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National Academy of Engineering 2011 U.S. Frontiers of Engineering Symposium September 19-21, 2011 Google, Inc. Mountain View, California Advancing Natural Language Understanding with Collaboratively Generated Content September 19, 2011 Presented by Dr. Evgeniy Gabrilovich. ABSTRACT: Google hosted 100 attendees of the 2011 Nat'l Academy of Engineering's U.S. Frontiers of Engineering symposium (FOE) at our Mountain View office and Dinah's Garden Hotel in Palo Alto. The symposium is an annual three-day meeting that brings together 100 of the nation's outstanding young engineers (ages 30-45) from industry, academia, and government to discuss pioneering technical and leading-edge research in various engineering fields and industry sectors. About the speaker: Dr. Evgeniy Gabrilovich is a Senior Research Scientist at Yahoo! in California. In his talk Dr. Gabrilovich provides an overview of using collaboratively generated content for representing the semantics of natural language, and discusses new information retrieval algorithms enabled by this representation.
Views: 3643 GoogleTechTalks
Bebe Rexha - I Can't Stop Drinking About You [Official Music Video]
 
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Check out the official music video for Bebe Rexha's "I Can't Stop Drinking About You"! Bebe Rexha's "I Don't Wanna Grow Up" EP is available now on iTunes! Download it here: smarturl.it/IDontWannaGrowUpEP LISTEN Available on iTunes: http://bit.ly/1ouIvWw Available on Spotify: http://smarturl.it/ICSDAYSpotify CONNECT WITH BEBE Offical Website: http://www.beberexha.com Facebook: https://www.facebook.com/Beberexha Twitter: http://www.twitter.com/BEBEREXHA Instagram: http://instagram.com/beberexha Youtube: http://www.youtube.com/BEBEREXHA Soundcloud: https://soundcloud.com/beberexha LYRICS No ones gonna love you like I do. No ones gonna care like I do. And I can feel it in the way that you breathe. I know you dream of her while you sleep next to me. I can't stop drinking about you. I gotta numb the pain. I can't stop drinking about you. Without you I ain't the same. So pour a shot in my glass and I'll forget forever! So pour a shot in my glass cause it makes everything better! Darlin tell me what more can I do? Don't you know that I was meant for you? You say I feel like heaven on earth, But You'd never know what heaven was if it wasn't for... her. I can't stop drinking about you. I gotta numb the pain. I can't stop drinking about you. Without you I ain't the same. So pour a shot in my glass and I'll forget forever! So pour a shot in my glass cause it makes everything better! I can't stop drinking about you. I can't stop drinking about you. No ones gonna love you like I do. I can't stop drinking about you. I can't stop drinking about you. So pour a shot in my glass and I'll forget forever! So pour a shot in my glass cause it makes everything better! No ones gonna love you like I do.
Views: 19613331 Bebe Rexha

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