Search results “Visualization data mining”
Data Mining : Data Visualization Techniques
This video explains various visualization techniques in data mining. Video Lecture by Anisha Lalwani.
Views: 1707 topNotch Tutorials
Introduction to Data Mining: Data Exploration & Visualization
In our last section in data mining fundamentals, we introduce you to data exploration and visualization and what they are to data mining. -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8MwZ0 See what our past attendees are saying here: https://hubs.ly/H0f8M9m0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 5084 Data Science Dojo
Basic Data Visualisation Techniques
Learn basic data visualization techniques in this tutorials. For Training & Study packs on Analytics/Data Science/Big Data, Contact us at [email protected] Find all free videos & study packs available with us here: http://analyticsuniversityblog.blogspot.in/ SUBSCRIBE TO THIS CHANNEL for free tutorials on Analytics/Data Science/Big Data/SAS/R/Hadoop
Views: 10571 Analytics University
DATA MINING   1 Data Visualization   3 1 1  Graphs and Networks
Views: 1279 Ryo Eng
DATA MINING   1 Data Visualization   4 1 1  Visualization Systems
Views: 45 Ryo Eng
The beauty of data visualization - David McCandless
View full lesson: http://ed.ted.com/lessons/david-mccandless-the-beauty-of-data-visualization David McCandless turns complex data sets, like worldwide military spending, media buzz, and Facebook status updates, into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. Talk by David McCandless.
Views: 548901 TED-Ed
DATA MINING   1 Data Visualization   4 2 1  Visualization System Design
Views: 28 Ryo Eng
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 130546 CS Dojo
DATA MINING   1 Data Visualization   2 0  Information
Views: 61 Ryo Eng
Data Visualization Design by Etan Lightstone: FutureStack 13
Data visualizations have become a first class citizen of information dissemination on the web, and a powerful tool when used effectively in product user interfaces . With technologies like D3, we are able to provide a great deal of interactivity to these visualizations, and with almost unlimited possibilities. This talk will be focusing on how to design effective data visualizations: * Design process for data viz * Visual design patterns to follow * Using the right charts * Data mining, and cutting through the noise of very large data sets Be sure to subscribe and follow New Relic at: https://twitter.com/NewRelic https://www.facebook.com/NewRelic https://www.youtube.com/NewRelicInc
Views: 51348 New Relic
Articles on Data Visualization in Data Mining
http://www.SystemsThinkingConsultant.com In this video Systems Thinking Consultant Ron Seiler discusses articles on data visualization in data mining, as well as, holistic views of knowledge management models.
Views: 153 abendegolove
DATA MINING   1 Data Visualization   3 1 3  Graph Visualization
Views: 158 Ryo Eng
58011070 Data Mining : Data Visualization
นางสาวลลิตา สรวมชีพ 58011070 sec 2 Data Mining 01236057
Mining Your Logs - Gaining Insight Through Visualization
Google Tech Talk (more info below) March 30, 2011 Presented by Raffael Marty. ABSTRACT In this two part presentation we will explore log analysis and log visualization. We will have a look at the history of log analysis; where log analysis stands today, what tools are available to process logs, what is working today, and more importantly, what is not working in log analysis. What will the future bring? Do our current approaches hold up under future requirements? We will discuss a number of issues and will try to figure out how we can address them. By looking at various log analysis challenges, we will explore how visualization can help address a number of them; keeping in mind that log visualization is not just a science, but also an art. We will apply a security lens to look at a number of use-cases in the area of security visualization. From there we will discuss what else is needed in the area of visualization, where the challenges lie, and where we should continue putting our research and development efforts. Speaker Info: Raffael Marty is COO and co-founder of Loggly Inc., a San Francisco based SaaS company, providing a logging as a service platform. Raffy is an expert and author in the areas of data analysis and visualization. His interests span anything related to information security, big data analysis, and information visualization. Previously, he has held various positions in the SIEM and log management space at companies such as Splunk, ArcSight, IBM research, and PriceWaterhouse Coopers. Nowadays, he is frequently consulted as an industry expert in all aspects of log analysis and data visualization. As the co-founder of Loggly, Raffy spends a lot of time re-inventing the logging space and - when not surfing the California waves - he can be found teaching classes and giving lectures at conferences around the world. http://about.me/raffy
Views: 25123 GoogleTechTalks
What is DATA VISUALIZATION? What does DATA VISUALIZATION mean? DATA VISUALIZATION meaning - DATA VISUALIZATION definition - DATA VISUALIZATION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Data visualization or data visualisation is viewed by many disciplines as a modern equivalent of visual communication. It involves the creation and study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information". A primary goal of data visualization is to communicate information clearly and efficiently via statistical graphics, plots and information graphics. Numerical data may be encoded using dots, lines, or bars, to visually communicate a quantitative message. Effective visualization helps users analyze and reason about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables. Data visualization is both an art and a science. It is viewed as a branch of descriptive statistics by some, but also as a grounded theory development tool by others. The rate at which data is generated has increased. Data created by internet activity and an expanding number of sensors in the environment, such as satellites, are referred to as "Big Data". Processing, analyzing and communicating this data present a variety of ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists have emerged to help address this challenge. Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn't mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose — to communicate information". Indeed, Fernanda Viegas and Martin M. Wattenberg have suggested that an ideal visualization should not only communicate clearly, but stimulate viewer engagement and attention. Not limited to the communication of an information, a well-crafted data visualization is also a way to a better understanding of the data (in a data-driven research perspective), as it helps uncover trends, realize insights, explore sources, and tell stories. Data visualization is closely related to information graphics, information visualization, scientific visualization, exploratory data analysis and statistical graphics. In the new millennium, data visualization has become an active area of research, teaching and development. According to Post et al. (2002), it has united scientific and information visualization.
Views: 2441 The Audiopedia
DATA MINING   1 Data Visualization   4 1 3  Database Visualization Part 1
Views: 52 Ryo Eng
Data Mining with Data Visualization: Keynote at Big Data Analysis and Data Mining, 2016
Keynote talk at the 3rd International Conference on Big Data Analysis and Data Mining, London, UK, 26-27 Sept 2016. Abstract: Some people believe that we live in the Age of Information. I believe it’s much more accurate to say we live in the Age of Data. With the rapid advancement of big data storage technologies and the ever-decreasing costs of hardware, our ability to derive and store data is unprecedented. However, a large gap remains between our ability to generate and store large collections of complex, time-dependent data and our ability to derive useful information and knowledge from it. Data visualization leverages our most powerful sense, vision, in order to derive knowledge and gain insight into large, multi-variate data sets that describe complicated and often time-dependent behavior. This talk presents an introduction into the world of data visualization with very different taster applications: Call Center Visualization, Computational Fluid Dynamics (CFD), marine biology, molecular dynamics, and rugby, showcasing some of visualizations strengths, weaknesses, and goals. The identity of Sally might be revealed during the talk. Connect with DataVis Bob on Facebook: https://www.facebook.com/datavisbob
Views: 205 DataVisBob Laramee
DATA MINING   1 Data Visualization   2 1 1  Data
Views: 74 Ryo Eng
DATA MINING   1 Data Visualization   2 2 1  Glyphs Part 2
Views: 28 Ryo Eng
Statistics 101 -  Data Visualization
Enroll in the Statistics course for free at: https://cognitiveclass.ai/courses/statistics-101/ Take this course and you won't fail statistics. Welcome to the Statistics 101 course, taught by Murtaza Haider, Assistant Professor at Ryerson University. Statistics is one of the most challenging topics to learn, but Murtaza brings a gentle introduction to statistics in practice. Learn about descriptive statistics, variance, probability, correlation, and data visualization. This Statistics 101 course ends with a fully-guided #statistics exercise exploring the “hot” topic of: do good looking professors get better teaching evaluations? A free trial of SPSS Statistics is included in this course. ABOUT THIS COURSE Split into five modules, this is a beginner's course covering the fundamentals of statistics. Start with mean, mode, and median. Then learn about standard deviation using examples from basketball. Learn about probability with dice. Learn what it means to group data by categorical variables, and how you can transform your data into appropriate graphs and charts. In the final module, using an open data set, learn whether good looking professors indeed get better teaching evaluations. This course is taught using SPSS Statistics. No prior experience necessary. A free trial is available through this course, available here: SPSS Statistics (Free Trial). Connect with Cognitive Class: https://www.facebook.com/cognitiveclass/ https://twitter.com/CognitiveClass https://www.linkedin.com/groups/4060416/profile
Views: 14174 Cognitive Class
Data Visualization Basics [Hindi]
How to visualize a data in Hindi
Views: 1122 Data Scientist
DATA MINING   1 Data Visualization   2 3 1  Tufte's Design Rules
Views: 267 Ryo Eng
DATA MINING   1 Data Visualization   3 2 2  Multidimensional Scaling
Views: 9173 Ryo Eng
RapidMiner Tutorial - Visualization  (Data Mining and Predictive Analytics System)
A tutorial discussing some of the visualization capabilities of RapidMiner, an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 10310 Predictive Analytics
DATA MINING   1 Data Visualization   3 2 1  Principal Component Analysis
Views: 555 Ryo Eng
DATA MINING   1 Data Visualization   2 1 3  Charts
Views: 74 Ryo Eng
DATA MINING   1 Data Visualization   2 1 2  Mapping
Views: 97 Ryo Eng
DATA MINING   1 Data Visualization   3 1 4  Tree Maps
Views: 744 Ryo Eng
Taro Data Mining and Visualization
Views: 25 Haoyang Li
Introduction of Orange:A data visualization and data mining tool.
Orange: A data visualization and data mining tool, drag and drop method to create neural networks. Easy tool to get start. For more information visit- www.matlabsolutions.com
Views: 22 MATLAB Solutions
DATA MINING   1 Data Visualization   3 0  Introduction
Views: 28 Ryo Eng
Advanced Data Mining with Weka (5.3: Visualization)
Advanced Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 3: Visualization http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/7XXl63 https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 2354 WekaMOOC
7. Text Mining Webinar - Visualization
This is the part about visualization from the Text Mining Webinar of October 30 2013 (https://www.youtube.com/edit?o=U&video_id=tY7vpTLYlIg). Visualization mainly covers two KNIME nodes: Tag Cloud and Document Viewer node.
Views: 2008 KNIMETV
What is Data Visualization?
This video is part of the UBC Learning Commons three-minute tutorials series. The tutorial will introduce you to the concepts of data visualization, provide examples of how it is done, and show you some online tools to get you started. Visit the UBC Learning Commons Study Toolkits: http://learningcommons.ubc.ca/get-started/study-toolkits/ or attend one of our online workshops: http://learningcommons.ubc.ca/get-started/learning-skills-resources/online-workshop-resources/
Data Mining with R & RStudio - KMeans Clustering and Visualization
Simple overview of data mining with R and RStudio.
Views: 2955 Gaurav Jetley
DATA MINING   1 Data Visualization   4 1 2  The Information Visualization Mantra Part 3
Views: 26 Ryo Eng
Data Mining : Visualization with Tableau
Home Assignment, the 3rd video.
Views: 1359 Ahram Kang
DATA MINING   1 Data Visualization   2 2 2  Parallel Coordinates
Views: 875 Ryo Eng
Data Mining : Visualization with Tableau
Home Assignment, the 6th video.
Views: 279 Ahram Kang
Data Mining : Visualization with Tableau
Home Assignment, the 4th video.
Views: 578 Ahram Kang
Janet Watson 2018: Data Mining and Visualization of Detrital Zircon Data
A Talk from Dean Meek (University of Saskatchewan) Wednesday 28 February 2018 Data Mining and Visualization of Detrital Zircon Data: Assessment of Palaeogeographic and Geodynamic Setting Using Data from Laurentia
Views: 101 GeologicalSociety
DATA MINING   1 Data Visualization   4 0 Introduction
Views: 17 Ryo Eng
Michael Conover: Information Visualization for Large-Scale Data Workflows
Presented at SF Data Mining on Oct 9, 2013 The ability to instrument and interrogate data as it moves through a processing pipeline is fundamental to effective machine learning at scale. Applied in this capacity, information visualization technologies drive product innovation, shorten iteration cycles, reduce uncertainty, and ultimately improve the performance of predictive models. It can be challenging, however, to understand where in a workflow to employ data visualization, and, once committed to doing so, developing revealing visualizations that suggest clear next steps can be similarly daunting. In this talk we'll describe the role that information visualization technologies play in the LinkedIn data science ecosystem, and explore best practices for understanding the structure of large-scale data in a production environment. From hypothesis generation and feature development to model evaluation and tooling, visualization is at the heart of LinkedIn's machine learning workflows, enabling our data scientists to reason and communicate more effectively. Broken down into clear, structured insights based on proven workflow patterns, this talk will help you understand how to apply information visualization to the analytical challenges you encounter every day.
Views: 4563 SF Data Mining
Synapse Visualization and Data Mining
Peltarion Synapse lets you explore and visualize your data and gives you an understanding of the task at hand. Use an array of powerful visualizers ranging from histograms to self organizing maps. Interconnect visualizers to create a hierarchical view that allows you to discover hidden relations and patterns. For more information see: http://www.peltarion.com/products/synapse
Views: 3076 Peltarion
Data Visualization in R Part-1
https://sites.google.com/site/raibharatendra/home/data-visualization Shows how to make graphs and charts in R. Examples include histogram, pie chart, bar chart, scatter plot, box plot, etc. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 6735 Bharatendra Rai
DATA MINING   1 Data Visualization   4 1 2  The Information Visualization Mantra Part 1
Views: 40 Ryo Eng

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