What is network analysis good for, and how can you apply it yourself using open source tools? A demo is shown, making a plot of the matatu bus network in Nairobi, Kenya.
De presentatie van Erwin Folmer, tijdens de parallelle sessie 'Randvoorwaarden voor data gedreven beleid en politiek' van het congres 'Data gedreven Beleidsontwikkeling' in Den Haag op 28 november 2017.
Drowning in information – the need of macroscopes for research fundingAndrea Scharnhorst
Andrea Scharnhorst (2015) Drowning in information – the need of macroscopes for research funding. Presentation at the international conference: PLANNING, PREDICTION, SCENARIOS - Using Simulations and Maps - 2015 Annual EA Conference - 11–12 May 2015 Bonn
1) The document discusses the evolution of the semantic web and linked data, from their initial visions to their current uses. It describes how linked data has focused more on sharing information as a graph and facilitating data integration, rather than the formal ontologies originally envisioned for the semantic web.
2) Key developments in linked data are highlighted, such as schema.org for web pages metadata and DBpedia for open data. However, limitations around costs, incentives and tool maintenance are noted.
3) Emerging areas are knowledge discovery through graph mining of linked data, and the potential for a more "sentient web" combining linked data with sensors and AI/ML for continuous learning.
The EnviroCar Platform: A Decentralized Approach to Monitoring Urban Traffic...Carsten Keßler
Presentation at Ground Transportation Technology Symposium: Big Data and Innovative Solutions for Safe,
Efficient and Sustainable Mobility. November 19, 2014 at
New York Institute of Technology (NYIT)
Research in the Age of the Context MachineCarsten Keßler
This document discusses research challenges in context-aware systems as context becomes more integrated into technology. It outlines the evolution from early location-based systems to modern context-aware systems that consider location as well as other contextual factors like weather, points of interest, connected devices, social relationships, schedules and interests. Three key research challenges are presented: 1) effective representation and integration of different types of context data, 2) determining what context is relevant for a given task and how this may differ between users, and 3) ensuring user privacy and control over what context data is shared while still enabling useful services.
The document discusses the Kadaster Knowledge Graph (KG) and LOKI system developed by Kadaster, the Dutch land registry. The KG links and integrates data from various sources to provide a unified view. It uses web standards like linked data to make the data interoperable, accessible, and reusable. LOKI is a question answering system built on top of the KG that allows users to ask questions about properties and receive location-based answers from integrated Kadaster and other data sources. The KG goes beyond traditional data publication approaches by making the data findable, accessible, interoperable, and reusable through open standards and decentralization.
De presentatie van Erwin Folmer, tijdens de parallelle sessie 'Randvoorwaarden voor data gedreven beleid en politiek' van het congres 'Data gedreven Beleidsontwikkeling' in Den Haag op 28 november 2017.
Drowning in information – the need of macroscopes for research fundingAndrea Scharnhorst
Andrea Scharnhorst (2015) Drowning in information – the need of macroscopes for research funding. Presentation at the international conference: PLANNING, PREDICTION, SCENARIOS - Using Simulations and Maps - 2015 Annual EA Conference - 11–12 May 2015 Bonn
1) The document discusses the evolution of the semantic web and linked data, from their initial visions to their current uses. It describes how linked data has focused more on sharing information as a graph and facilitating data integration, rather than the formal ontologies originally envisioned for the semantic web.
2) Key developments in linked data are highlighted, such as schema.org for web pages metadata and DBpedia for open data. However, limitations around costs, incentives and tool maintenance are noted.
3) Emerging areas are knowledge discovery through graph mining of linked data, and the potential for a more "sentient web" combining linked data with sensors and AI/ML for continuous learning.
The EnviroCar Platform: A Decentralized Approach to Monitoring Urban Traffic...Carsten Keßler
Presentation at Ground Transportation Technology Symposium: Big Data and Innovative Solutions for Safe,
Efficient and Sustainable Mobility. November 19, 2014 at
New York Institute of Technology (NYIT)
Research in the Age of the Context MachineCarsten Keßler
This document discusses research challenges in context-aware systems as context becomes more integrated into technology. It outlines the evolution from early location-based systems to modern context-aware systems that consider location as well as other contextual factors like weather, points of interest, connected devices, social relationships, schedules and interests. Three key research challenges are presented: 1) effective representation and integration of different types of context data, 2) determining what context is relevant for a given task and how this may differ between users, and 3) ensuring user privacy and control over what context data is shared while still enabling useful services.
The document discusses the Kadaster Knowledge Graph (KG) and LOKI system developed by Kadaster, the Dutch land registry. The KG links and integrates data from various sources to provide a unified view. It uses web standards like linked data to make the data interoperable, accessible, and reusable. LOKI is a question answering system built on top of the KG that allows users to ask questions about properties and receive location-based answers from integrated Kadaster and other data sources. The KG goes beyond traditional data publication approaches by making the data findable, accessible, interoperable, and reusable through open standards and decentralization.
Context-free data analysis with Transcendental Information Cascades.Markus Luczak-Rösch
In order to discover hidden relationships and patterns in data streams from multiple heterogenous sources, we work on a method for exploratory data analysis. We disregard any system-specific context to generate generic networks of information co-occurrence. These networks allow for more informed sampling and filtering. Case specific context can be added once these networks have been created to support accurate decision making.
This document provides an introduction to the European Grid Infrastructure (EGI). It explains that EGI is a federated computing infrastructure that provides access to computing resources and data storage across over 30 European countries. EGI supports researchers from many disciplines through reliable ICT services and currently connects over 340 resource centers that provide over 435,000 CPU cores, 190 petabytes of disk storage, and 180 petabytes of tape storage. Key users of EGI include high energy physics, astronomy, life sciences, and earth sciences research communities.
Significant Role of Statistics in Computational SciencesEditor IJCATR
This paper is focused on the issues related to optimizing statistical approaches in the emerging fields of Computer Science
and Information Technology. More emphasis has been given on the role of statistical techniques in modern data mining. Statistics is
the science of learning from data and of measuring, controlling, and communicating uncertainty. Statistical approaches can play a vital
role for providing significance contribution in the field of software engineering, neural network, data mining, bioinformatics and other
allied fields. Statistical techniques not only helps make scientific models but it quantifies the reliability, reproducibility and general
uncertainty associated with these models. In the current scenario, large amount of data is automatically recorded with computers and
managed with the data base management systems (DBMS) for storage and fast retrieval purpose. The practice of examining large preexisting
databases in order to generate new information is known as data mining. Presently, data mining has attracted substantial
attention in the research and commercial arena which involves applications of a variety of statistical techniques. Twenty years ago
mostly data was collected manually and the data set was in simple form but in present time, there have been considerable changes in
the nature of data. Statistical techniques and computer applications can be utilized to obtain maximum information with the fewest
possible measurements to reduce the cost of data collection.
This document outlines plans for the Clariah Structured Data Hub project. Clariah aims to provide humanities scholars access to large digital resources and tools to enable ground-breaking research. The Structured Data Hub will curate and link structured datasets on various levels from micro to macro. It will also create tools to facilitate the research process, such as data evaluation, linking, analysis, and visualization. The project will involve a design phase with two pilot studies, followed by preparation, execution, and close phases to develop a research infrastructure with linked data and tools.
The document discusses architecting an audio plugin host as a web extension. It proposes a solution where the web extension acts as a host for a set of audio plugins and processors. This would allow arbitrary connections between plugins and both simple and advanced audio processing directly within the browser without external hardware. The key challenges are sharing data between the foreground and background processes of the web extension and ensuring adequate performance.
Open Belgium 5-star linked open data address registryRaf Buyle
This session reports on the development of the 5-star Linked Open Data Address Register.
The first product released by the Flemish Government in line with the Linked Data principles is the Central Reference Address Database (CRAB), containing well over 4 million addresses and their geographical coordinates. The addresses are synchronised in real time between 308 local governments and the Linked Base registry.
The document discusses information modeling and provides examples of how to create an effective information model. It describes how information modeling was first defined in 1976 and involves representing concepts, relationships, and rules for a domain. The document then gives examples of why information modeling is useful today for sharing concepts, specifications, and determining technology requirements. It provides guidance on how to effectively scope an information modeling project through interviewing stakeholders and capturing concepts through unbiased questioning and listening. Finally, it demonstrates how to organize concepts in modeling tools like Gra.fo by defining properties and relationships to avoid being an inexperienced "Wimpy Model Manager".
Convergence for Scientific Method - HPC, AI, Simulation and Experimentinside-BigData.com
In this deck from the UK HPC Conference, Alan Real from Durham University presents: Convergence for Scientific Method - HPC, AI, Simulation and Experiment.
"This talk will discuss how advances in instrumentation have caused many new areas to embrace HPC and AI in order to successfully conduct and understand their experiments."
Watch the video: https://wp.me/p3RLHQ-l0B
Learn more: http://hpcadvisorycouncil.com/events/2019/uk-conference/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Big Data has shaped much of the tech innovation happening around the world today giving people immense power to make sense of large blobs of structured and unstructured data.
Join Riju Saha, Digital Excellence Head, Oracle COE at Tata Consultancy Services to decode the fundamentals of Big data and how can you build a career in this fascinating field.
Data science uses scientific methods and algorithms to extract knowledge and insights from structured and unstructured data. It unifies statistics, data analysis, machine learning and related methods. Data science is important for business as it can turn ideas from science fiction into reality and help make predictions and decisions using predictive analytics, machine learning and analyzing vast amounts of business data. Data science projects involve tasks like data cleaning, exploratory analysis, visualization, machine learning and communication. Data science education is evolving to produce professionals with skills in computer science, information science, and statistics.
This document discusses the need for a new digital research infrastructure for the arts and humanities called DARIAH. It outlines how humanities research is increasingly relying on large digital datasets and resources requiring networked infrastructure. The document describes how DARIAH would provide access to digitized cultural heritage resources and tools to analyze these resources. It also discusses the organizational structure and partnerships needed to establish DARIAH and ensure its long-term sustainability to support innovative digital humanities research across Europe.
This document contains the resume of Balaji Sharma, who has 4+ years of experience in data-driven technical marketing and strategic post-sales engagements. He has a PhD in Mechanical Engineering from the University of Cincinnati and strong skills in data analysis, visualization, programming, and engineering. His experience includes developing data frameworks, performing data analysis, technical evangelism, and research assistant roles involving multi-agent robotics systems and wildfire tracking.
MITProfessionalX DSx Certificate | MIT Professional Education Digital ProgramsAdolfo Norì
Adolfo Norì has successfully completed the MIT Professional Education course "Data Science: Data to Insights" from October 4th to November 15th, 2016. This is certified by Bhaskar Pant, Executive Director of MIT Professional Education, Devavrat Shah, Professor and Director of Statistics and Data Science Center at MIT, and Philippe Rigollet, Associate Professor at MIT in the Department of Mathematics, IDSS, LIDS, Statistics and Data Science Center and Broad Institute.
The document provides a history of data science and artificial intelligence, discusses how the two fields intersect, and provides examples of practical coding techniques for data scientists using AI tools. It begins with a brief history of data science from the 1960s development of empirical data analysis to the modern role of data scientists. It then discusses the parallel history of AI from its origins in the 1950s to recent advances in deep learning. The document explains that data scientists today can focus on analysis or building machine learning models, and that Python is a common coding language in both fields. It offers Jupyter Notebooks, Google Collab, and Docker as tools and provides examples using sentiment analysis, Google AutoML, and AWS DeepLens.
MINING AND VISUALIZING USAGE OF EDUCATIONAL SYSTEMS USING LINKED DATAMartin Ebner
This document presents a methodology for mining and visualizing usage data from educational systems using linked data. The methodology is demonstrated on a case study of a personal learning environment (PLE) with over 4000 users. Usage logs from the PLE over two years were modeled as semantic web data and queried to generate visualizations of usage intensity and comparisons. The visualizations provide insights that can help improve system usability and design. Future work includes enhancing the methodology with linked data and improving recommendations.
The document discusses dealing with digital, data-driven scholarship in the humanities, including working with raw data through tools like MySQL, text wrangler, and grep codes, and then experimenting through sketching, manipulating, and visualizing the data. It also addresses infrastructure needs for digital humanities projects like server space, open access repositories, and data management planning. The document provides information about the author Amanda Licastro and links to related resources.
Chinese food is about more than just satisfying hunger. It is closely connected to Chinese culture and spirituality. Rice is the staple food and vegetarianism is very common due to religious influences. Chinese dishes often include pork, chicken and vegetables, but seafood is most prominent in Hong Kong cuisine. A variety of fruits are also available. Business is often conducted over meals. Chopsticks are traditionally used for eating and guests should follow this custom when dining in Chinese homes or restaurants. Food is placed in the center of the table for diners to serve themselves rice and portions from shared dishes. While Chinese restaurants are plentiful, Hong Kong offers diverse cuisines from around the world as well.
Context-free data analysis with Transcendental Information Cascades.Markus Luczak-Rösch
In order to discover hidden relationships and patterns in data streams from multiple heterogenous sources, we work on a method for exploratory data analysis. We disregard any system-specific context to generate generic networks of information co-occurrence. These networks allow for more informed sampling and filtering. Case specific context can be added once these networks have been created to support accurate decision making.
This document provides an introduction to the European Grid Infrastructure (EGI). It explains that EGI is a federated computing infrastructure that provides access to computing resources and data storage across over 30 European countries. EGI supports researchers from many disciplines through reliable ICT services and currently connects over 340 resource centers that provide over 435,000 CPU cores, 190 petabytes of disk storage, and 180 petabytes of tape storage. Key users of EGI include high energy physics, astronomy, life sciences, and earth sciences research communities.
Significant Role of Statistics in Computational SciencesEditor IJCATR
This paper is focused on the issues related to optimizing statistical approaches in the emerging fields of Computer Science
and Information Technology. More emphasis has been given on the role of statistical techniques in modern data mining. Statistics is
the science of learning from data and of measuring, controlling, and communicating uncertainty. Statistical approaches can play a vital
role for providing significance contribution in the field of software engineering, neural network, data mining, bioinformatics and other
allied fields. Statistical techniques not only helps make scientific models but it quantifies the reliability, reproducibility and general
uncertainty associated with these models. In the current scenario, large amount of data is automatically recorded with computers and
managed with the data base management systems (DBMS) for storage and fast retrieval purpose. The practice of examining large preexisting
databases in order to generate new information is known as data mining. Presently, data mining has attracted substantial
attention in the research and commercial arena which involves applications of a variety of statistical techniques. Twenty years ago
mostly data was collected manually and the data set was in simple form but in present time, there have been considerable changes in
the nature of data. Statistical techniques and computer applications can be utilized to obtain maximum information with the fewest
possible measurements to reduce the cost of data collection.
This document outlines plans for the Clariah Structured Data Hub project. Clariah aims to provide humanities scholars access to large digital resources and tools to enable ground-breaking research. The Structured Data Hub will curate and link structured datasets on various levels from micro to macro. It will also create tools to facilitate the research process, such as data evaluation, linking, analysis, and visualization. The project will involve a design phase with two pilot studies, followed by preparation, execution, and close phases to develop a research infrastructure with linked data and tools.
The document discusses architecting an audio plugin host as a web extension. It proposes a solution where the web extension acts as a host for a set of audio plugins and processors. This would allow arbitrary connections between plugins and both simple and advanced audio processing directly within the browser without external hardware. The key challenges are sharing data between the foreground and background processes of the web extension and ensuring adequate performance.
Open Belgium 5-star linked open data address registryRaf Buyle
This session reports on the development of the 5-star Linked Open Data Address Register.
The first product released by the Flemish Government in line with the Linked Data principles is the Central Reference Address Database (CRAB), containing well over 4 million addresses and their geographical coordinates. The addresses are synchronised in real time between 308 local governments and the Linked Base registry.
The document discusses information modeling and provides examples of how to create an effective information model. It describes how information modeling was first defined in 1976 and involves representing concepts, relationships, and rules for a domain. The document then gives examples of why information modeling is useful today for sharing concepts, specifications, and determining technology requirements. It provides guidance on how to effectively scope an information modeling project through interviewing stakeholders and capturing concepts through unbiased questioning and listening. Finally, it demonstrates how to organize concepts in modeling tools like Gra.fo by defining properties and relationships to avoid being an inexperienced "Wimpy Model Manager".
Convergence for Scientific Method - HPC, AI, Simulation and Experimentinside-BigData.com
In this deck from the UK HPC Conference, Alan Real from Durham University presents: Convergence for Scientific Method - HPC, AI, Simulation and Experiment.
"This talk will discuss how advances in instrumentation have caused many new areas to embrace HPC and AI in order to successfully conduct and understand their experiments."
Watch the video: https://wp.me/p3RLHQ-l0B
Learn more: http://hpcadvisorycouncil.com/events/2019/uk-conference/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Big Data has shaped much of the tech innovation happening around the world today giving people immense power to make sense of large blobs of structured and unstructured data.
Join Riju Saha, Digital Excellence Head, Oracle COE at Tata Consultancy Services to decode the fundamentals of Big data and how can you build a career in this fascinating field.
Data science uses scientific methods and algorithms to extract knowledge and insights from structured and unstructured data. It unifies statistics, data analysis, machine learning and related methods. Data science is important for business as it can turn ideas from science fiction into reality and help make predictions and decisions using predictive analytics, machine learning and analyzing vast amounts of business data. Data science projects involve tasks like data cleaning, exploratory analysis, visualization, machine learning and communication. Data science education is evolving to produce professionals with skills in computer science, information science, and statistics.
This document discusses the need for a new digital research infrastructure for the arts and humanities called DARIAH. It outlines how humanities research is increasingly relying on large digital datasets and resources requiring networked infrastructure. The document describes how DARIAH would provide access to digitized cultural heritage resources and tools to analyze these resources. It also discusses the organizational structure and partnerships needed to establish DARIAH and ensure its long-term sustainability to support innovative digital humanities research across Europe.
This document contains the resume of Balaji Sharma, who has 4+ years of experience in data-driven technical marketing and strategic post-sales engagements. He has a PhD in Mechanical Engineering from the University of Cincinnati and strong skills in data analysis, visualization, programming, and engineering. His experience includes developing data frameworks, performing data analysis, technical evangelism, and research assistant roles involving multi-agent robotics systems and wildfire tracking.
MITProfessionalX DSx Certificate | MIT Professional Education Digital ProgramsAdolfo Norì
Adolfo Norì has successfully completed the MIT Professional Education course "Data Science: Data to Insights" from October 4th to November 15th, 2016. This is certified by Bhaskar Pant, Executive Director of MIT Professional Education, Devavrat Shah, Professor and Director of Statistics and Data Science Center at MIT, and Philippe Rigollet, Associate Professor at MIT in the Department of Mathematics, IDSS, LIDS, Statistics and Data Science Center and Broad Institute.
The document provides a history of data science and artificial intelligence, discusses how the two fields intersect, and provides examples of practical coding techniques for data scientists using AI tools. It begins with a brief history of data science from the 1960s development of empirical data analysis to the modern role of data scientists. It then discusses the parallel history of AI from its origins in the 1950s to recent advances in deep learning. The document explains that data scientists today can focus on analysis or building machine learning models, and that Python is a common coding language in both fields. It offers Jupyter Notebooks, Google Collab, and Docker as tools and provides examples using sentiment analysis, Google AutoML, and AWS DeepLens.
MINING AND VISUALIZING USAGE OF EDUCATIONAL SYSTEMS USING LINKED DATAMartin Ebner
This document presents a methodology for mining and visualizing usage data from educational systems using linked data. The methodology is demonstrated on a case study of a personal learning environment (PLE) with over 4000 users. Usage logs from the PLE over two years were modeled as semantic web data and queried to generate visualizations of usage intensity and comparisons. The visualizations provide insights that can help improve system usability and design. Future work includes enhancing the methodology with linked data and improving recommendations.
The document discusses dealing with digital, data-driven scholarship in the humanities, including working with raw data through tools like MySQL, text wrangler, and grep codes, and then experimenting through sketching, manipulating, and visualizing the data. It also addresses infrastructure needs for digital humanities projects like server space, open access repositories, and data management planning. The document provides information about the author Amanda Licastro and links to related resources.
Chinese food is about more than just satisfying hunger. It is closely connected to Chinese culture and spirituality. Rice is the staple food and vegetarianism is very common due to religious influences. Chinese dishes often include pork, chicken and vegetables, but seafood is most prominent in Hong Kong cuisine. A variety of fruits are also available. Business is often conducted over meals. Chopsticks are traditionally used for eating and guests should follow this custom when dining in Chinese homes or restaurants. Food is placed in the center of the table for diners to serve themselves rice and portions from shared dishes. While Chinese restaurants are plentiful, Hong Kong offers diverse cuisines from around the world as well.
Eco world 14 Sept 2014-Renesial Leong asia's Queen of Propertykumar5367
The document discusses the current state of the Malaysian property market, challenges, opportunities and advice for investing. It notes that while there are challenges like GST and inflation, the market remains stable with steady population growth, economic development projects, and low interest rates. It recommends investing in residential properties, especially apartments and landed properties with good infrastructure, as the best way to benefit from capital appreciation and the necessity of housing. The overall message is that despite challenges, now is a good time to invest in property for long-term wealth creation.
The document discusses the evolution of pricing strategies over time from primitive to more sophisticated approaches. It outlines a continuum from reactive, cost-plus pricing to pre-emptive, value-based pricing that incorporates extensive customer insights and experimentation. The diagram shows increasing levels of pricing sophistication from supply-factor pricing through various special pricing approaches to ultimately optimized prices that dynamically adapt based on perceived customer value.
Five Trends in Analytics - How to Take Advantage Today - StampedeCon 2013StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, ohn Lucker, Partner and Principal at Deloitte Consulting, discussed Five Trends in Analytics - How to Take Advantage Today. Lucker will discuss the latest advancements in the world of analytics and offer strategies for tapping into their potential. The topic areas include visualization and design, mobile analytics and strategy analytics.
Optimaliseer je winst met betere pricing. Bekijk enkele mogelijkheden om met prijsstrategie meer winst te realiseren. Toont voorbeelden van prijsdifferentiatie, conjunct analyse, kortingswaterval en psychologische prijsfactoren.
Storm – Streaming Data Analytics at Scale - StampedeCon 2014StampedeCon
At StampedeCon 2014, Scott Shaw (Hortonworks) and Kit Menke (Enteprise Holdings) presented "Storm – Streaming Data Analytics at Scale"
Storm’s primary purpose is to provide real-time analytics against fast moving data before its stored. The use cases range from fraud detection, machine learning, to ETL.
Storm has been clocked at over 1 million tuples processed per second per node. It’s fast, scalable, and language agnostic. This session provides an architecture overview as well as a real-world discussion of its use and implementation at Enterprise Holdings.
Abstract:
Following the state of the art is paramount for sound and impact scientific practices informed strategic R&D decisions. This seminar seeks two main contributions: (i) providing a 10,000 foot view of 10 selected hot topics in networking, and (ii) Overview of recent practices in scientific events (e.g. Digitalization, Submission deadlines revisited, Open Science, Artifact Review Badging).
The 10 selected hot topics are as follows:
Intent-Based Networking (IBN)
Zero-Touch Management (ZTM)
Digital Twins (Networking for Digital Twins & Network Digital Twins)
Metaverse
Blockchain Networking
AI/ML (Network protocols meet AI/ML, Machine Learning for Networking)
High precision networking
Quantum Communications & Computing
6G (Beyond 5G)
OpenRAN
A Keynote at the Web Science Conference, 2018, held at the VU Amsterdam [1]. This describes in the main the output of the Semantic Technology Institute International (STI2) Summit (for senior researchers in the Semantic Web field) held in Crete in September, 2017 [2].
1. https://websci18.webscience.org/
2. https://www.sti2.org/events/2017-sti2-semantic-summit
The document provides an overview of the data mining concepts and techniques course offered at the University of Illinois at Urbana-Champaign. It discusses the motivation for data mining due to abundant data collection and the need for knowledge discovery. It also describes common data mining functionalities like classification, clustering, association rule mining and the most popular algorithms used.
This document provides an introduction to data mining concepts and techniques. It discusses why data mining is needed due to the massive growth of data. It defines data mining as the extraction of interesting patterns from large datasets. The document outlines the key steps in the knowledge discovery process and how data mining fits within business intelligence applications. It also describes different types of data that can be mined and popular data mining algorithms.
Data Science at Scale - The DevOps ApproachMihai Criveti
DevOps Practices for Data Scientists and Engineers
1 Data Science Landscape
2 Process and Flow
3 The Data
4 Data Science Toolkit
5 Cloud Computing Solutions
6 The rise of DevOps
7 Reusable Assets and Practices
8 Skills Development
Unit 1 (Chapter-1) on data mining concepts.pptPadmajaLaksh
This document provides an introduction to data mining concepts. It discusses why data mining is important due to the massive growth of data. It defines data mining as the automated analysis of large datasets to discover hidden patterns and unknown correlations. The document presents a multi-dimensional view of data mining, including the types of data that can be mined, the patterns that can be discovered, techniques used, and applications. It provides an overview of the key concepts in data mining.
This document summarizes a live webinar about creating and querying a graph database of Olympic data. It describes loading data on athletes, countries, sports, events and medals from 1896-2012 into a Neo4j graph database. It then demonstrates several example queries of the Olympic graph, such as the number of sports per games, medals per country per sport, and athletes who medaled in multiple sports.
This document provides an introduction to data mining concepts and techniques. It discusses why data mining is needed due to the massive growth of data, defines data mining as the extraction of patterns from large data sets, and outlines the data mining process. A variety of data types that can be mined are described, including relational, transactional, time-series, text and web data. The document also covers major data mining functionalities like classification, clustering, association rule mining and trend analysis. Top 10 popular data mining algorithms are listed.
The document provides an introduction to data mining. It discusses the growth of data from terabytes to petabytes and how data mining can help extract knowledge from large datasets. The document outlines the evolution of sciences from empirical to theoretical to computational and now data-driven. It also describes the evolution of database technology and defines data mining as the process of discovering interesting patterns from large amounts of data. The key steps of the knowledge discovery process are discussed.
It is a seminar project made by me . It is about the the data science and it's uses. As computer science student this is a important to manage the data and how to deal with easily and efficiently.
Big social data analytics - social network analysis Jari Jussila
This document discusses social network analysis and visualization of Twitter data using tools like Gephi. It provides steps to collect Twitter data using an API script, create a network file from the data, and calculate network metrics and visualize the network in Gephi. Key aspects covered include extracting tweet data, creating a network file with NetworkX, uploading files to PythonAnywhere to run the script, and analyzing and visualizing the resulting network in Gephi to understand information diffusion on Twitter.
Big Data Applications & Analytics Motivation: Big Data and the Cloud; Centerp...Geoffrey Fox
Motivating Introduction to MOOC on Big Data from an applications point of view https://bigdatacoursespring2014.appspot.com/course
Course says:
Geoffrey motivates the study of X-informatics by describing data science and clouds. He starts with striking examples of the data deluge with examples from research, business and the consumer. The growing number of jobs in data science is highlighted. He describes industry trend in both clouds and big data.
He introduces the cloud computing model developed at amazing speed by industry. The 4 paradigms of scientific research are described with growing importance of data oriented version. He covers 3 major X-informatics areas: Physics, e-Commerce and Web Search followed by a broad discussion of cloud applications. Parallel computing in general and particular features of MapReduce are described. He comments on a data science education and the benefits of using MOOC's.
Big Data Applications & Analytics Motivation: Big Data and the Cloud; Center...Geoffrey Fox
Motivating Introduction to MOOC on Big Data from an applications point of view https://bigdatacoursespring2014.appspot.com/course
Course says:
Geoffrey motivates the study of X-informatics by describing data science and clouds. He starts with striking examples of the data deluge with examples from research, business and the consumer. The growing number of jobs in data science is highlighted. He describes industry trend in both clouds and big data.
He introduces the cloud computing model developed at amazing speed by industry. The 4 paradigms of scientific research are described with growing importance of data oriented version. He covers 3 major X-informatics areas: Physics, e-Commerce and Web Search followed by a broad discussion of cloud applications. Parallel computing in general and particular features of MapReduce are described. He comments on a data science education and the benefits of using MOOC's.
The document provides an introduction to the concept of data mining. It discusses the evolution of data analysis techniques from empirical to computational to data-driven approaches. Data mining is presented as a natural evolution to analyze massive data sets and discover useful patterns. Key aspects of data mining covered include its functionality, types of data and knowledge that can be mined, major issues, and its relationship to other fields such as machine learning, statistics, and databases.
This document discusses big data mining and the Internet of Things. It first presents challenges with big data mining including modeling big data characteristics, identifying key challenges, and issues with statistical analysis of IoT data. It then describes an architecture called IOT-StatisticDB that provides a generalized schema for storing sensor data from IoT devices and a distributed system for parallel computing and statistical analysis of IoT big data. The system includes query operators for data retrieval and statistical analysis of IoT data in areas like transportation networks.
This document discusses big data mining and the Internet of Things. It first presents challenges with big data mining including modeling big data characteristics, identifying key challenges, and issues with statistical analysis of IoT data. It then describes an architecture called IOT-StatisticDB that provides a generalized schema for storing sensor data from IoT devices and a distributed system for parallel computing and statistical analysis of IoT big data. The system includes query operators for data retrieval and statistical analysis of IoT data in areas like transportation networks.
This document provides an introduction to data mining. It discusses the evolution of data mining technology, defines what data mining is, and outlines common data mining tasks like classification, clustering, and association rule discovery. The document also examines the KDD process, different types of data that can be mined, and major issues in data mining like scalability, handling diverse data types, and integrating discovered knowledge.
Social Network Analysis Introduction including Data Structure Graph overview. Doug Needham
Social Network Analysis Introduction including Data Structure Graph overview. Given in Cincinnati August 18th 2015 as part of the DataSeed Meetup group.
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This PowerPoint compilation offers a comprehensive overview of 20 leading innovation management frameworks and methodologies, selected for their broad applicability across various industries and organizational contexts. These frameworks are valuable resources for a wide range of users, including business professionals, educators, and consultants.
Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
This compilation is ideal for anyone looking to enhance their understanding of innovation management and drive meaningful change within their organization. Whether you aim to improve product development processes, enhance customer experiences, or drive digital transformation, these frameworks offer valuable insights and tools to help you achieve your goals.
INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
How MJ Global Leads the Packaging Industry.pdfMJ Global
MJ Global's success in staying ahead of the curve in the packaging industry is a testament to its dedication to innovation, sustainability, and customer-centricity. By embracing technological advancements, leading in eco-friendly solutions, collaborating with industry leaders, and adapting to evolving consumer preferences, MJ Global continues to set new standards in the packaging sector.
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
Digital Marketing with a Focus on Sustainabilitysssourabhsharma
Digital Marketing best practices including influencer marketing, content creators, and omnichannel marketing for Sustainable Brands at the Sustainable Cosmetics Summit 2024 in New York
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Discover timeless style with the 2022 Vintage Roman Numerals Men's Ring. Crafted from premium stainless steel, this 6mm wide ring embodies elegance and durability. Perfect as a gift, it seamlessly blends classic Roman numeral detailing with modern sophistication, making it an ideal accessory for any occasion.
https://rb.gy/usj1a2
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Storytelling is an incredibly valuable tool to share data and information. To get the most impact from stories there are a number of key ingredients. These are based on science and human nature. Using these elements in a story you can deliver information impactfully, ensure action and drive change.
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
SATTA MATKA SATTA FAST RESULT KALYAN TOP MATKA RESULT KALYAN SATTA MATKA FAST RESULT MILAN RATAN RAJDHANI MAIN BAZAR MATKA FAST TIPS RESULT MATKA CHART JODI CHART PANEL CHART FREE FIX GAME SATTAMATKA ! MATKA MOBI SATTA 143 spboss.in TOP NO1 RESULT FULL RATE MATKA ONLINE GAME PLAY BY APP SPBOSS