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Search results “Processes in data mining”
How data mining works
 
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In this video we describe data mining, in the context of knowledge discovery in databases. More videos on classification algorithms can be found at https://www.youtube.com/playlist?list=PLXMKI02h3_qjYoX-f8uKrcGqYmaqdAtq5 Please subscribe to my channel, and share this video with your peers!
Views: 204824 Thales Sehn Körting
Data Mining Process and CRISP DM - Cognitir
 
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This cognitorial provides an introduction to the data mining process with a focus on CRISP-DM. This video was created by Cognitir (formerly Import Classes). For additional free resources, visit: www.cognitir.com
Views: 12045 Cognitir
Data Mining
 
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KDD Process & DM Architecture
Views: 11694 Gotlur Karuna
Data Mining   KDD Process
 
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KDD - knowledge discovery in Database. short introduction on Data cleaning,Data integration, Data selection,Data mining,pattern evaluation and knowledge representation.
Introduction to data mining and architecture  in hindi
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 156267 Last moment tuitions
KDD ( knowledge data discovery )  in data mining in hindi
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 54517 Last moment tuitions
How Data Minng works or The KDD Process
 
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This video explains about the process of knowledge discovery in databases.
Views: 9877 kalyani chandra
Last Minute Tutorials | Data mining | Introduction | Examples
 
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NOTES:- Theory of computation : https://viden.io/knowledge/theory-of-computation?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 DAA(all topics are included in this link) : https://viden.io/knowledge/design-and-analysis-of-algorithms-topic-wise-ada?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Advanced DBMS : https://viden.io/knowledge/advanced-dbms?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 for QM method-https://viden.io/knowledge/quine-mccluskey-method-qm-method?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 K-MAPS : https://viden.io/knowledge/k-maps-karnaugh-map?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Basics of logic gates : https://viden.io/knowledge/basics-of-logic-gates-and-more?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Website: https://lmtutorials.com/ Facebook: https://www.facebook.com/Last-Minute-Tutorials-862868223868621/ For any queries or suggestions, kindly mail at: [email protected]
Views: 32235 Last Minute Tutorials
Introduction to Process Mining: Turning (Big) Data into Real Value
 
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With process mining, you can make your process visible in less than 5 minutes, based on log data you already have in your IT systems. Learn what process mining is, and how it works, in less than 2 minutes! (Animation work by 908video)
Views: 64898 P2Mchannel
Data Mining (Introduction for Business Students)
 
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This short revision video introduces the concept of data mining. Data mining is the process of analysing data from different perspectives and summarising it into useful information, including discovery of previously unknown interesting patterns, unusual records or dependencies. There are many potential business benefits from effective data mining, including: Identifying previously unseen relationships between business data sets Better predicting future trends & behaviours Extract commercial (e.g. performance insights) from big data sets Generating actionable strategies built on data insights (e.g. positioning and targeting for market segments) Data mining is a particularly powerful series of techniques to support marketing competitiveness. Examples include: Sales forecasting: analysing when customers bought to predict when they will buy again Database marketing: examining customer purchasing patterns and looking at the demographics and psychographics of customers to build predictive profiles Market segmentation: a classic use of data mining, using data to break down a market into meaningful segments like age, income, occupation or gender E-commerce basket analysis: using mined data to predict future customer behavior by past performance, including purchases and preferences
Views: 2177 tutor2u
Data mining process
 
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Views: 25542 Gio
What is Data Mining and its process
 
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Data mining , What is data mining and how data mining work.. and its process data is a computational process of finding patterns in hidden data in database ...also called KDD , Knowledge discovery database..
Views: 263 Zuhair Khan
Process Data Mining
 
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Views: 440 Lynn Langit
What is Data Mining
 
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Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term is a buzzword, and is frequently misused to mean any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) but is also generalized to any kind of computer decision support system, including artificial intelligence, machine learning, and business intelligence. In the proper use of the word, the key term is discovery[citation needed], commonly defined as "detecting something new". Even the popular book "Data mining: Practical machine learning tools and techniques with Java"(which covers mostly machine learning material) was originally to be named just "Practical machine learning", and the term "data mining" was only added for marketing reasons. Often the more general terms "(large scale) data analysis", or "analytics" -- or when referring to actual methods, artificial intelligence and machine learning -- are more appropriate. The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection) and dependencies (association rule mining). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting are part of the data mining step, but do belong to the overall KDD process as additional steps.
Views: 51913 John Paul
knowledge discovery process in data mining
 
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for more videos subscribe my channel!!!! https://youtu.be/sRDSW_jL-e4
Views: 163 AnA Tech
Data Mining & Business Intelligence | Tutorial #10 | Data Cleaning Process
 
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Order my books at 👉 http://www.tek97.com/ Handing Missing values and reducing the noisy data are the two techniques by which data cleaning initiates in data mining towards knowledge extraction. Watch now ! إن تسليم القيم المفقودة وتقليل البيانات المزعجة هما الأسلوبان اللذان يبدأ بهما تنظيف البيانات في استخراج البيانات نحو استخراج المعرفة. شاهد الآن ! La gestion des valeurs manquantes et la réduction des données bruitées sont les deux techniques par lesquelles le nettoyage des données débute dans l'extraction de données vers l'extraction des connaissances. Regarde maintenant ! La entrega de valores perdidos y la reducción de datos ruidosos son las dos técnicas mediante las cuales se inicia la limpieza de datos en la extracción de datos hacia la extracción de conocimiento. Ver ahora ! Übergeben Fehlende Werte und das Reduzieren der verrauschten Daten sind die beiden Techniken, mit denen die Datenbereinigung beim Data Mining zur Wissensextraktion initiiert wird. Schau jetzt ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1616 Ranji Raj
Data Cleaning Process Steps / Phases [Data Mining] Easiest Explanation Ever (Hindi)
 
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Last Minute Tutorials | KDD | Knowledge Discovery of Data
 
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NOTES:- Theory of computation : https://viden.io/knowledge/theory-of-computation?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 DAA(all topics are included in this link) : https://viden.io/knowledge/design-and-analysis-of-algorithms-topic-wise-ada?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Advanced DBMS : https://viden.io/knowledge/advanced-dbms?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 for QM method-https://viden.io/knowledge/quine-mccluskey-method-qm-method?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 K-MAPS : https://viden.io/knowledge/k-maps-karnaugh-map?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Basics of logic gates : https://viden.io/knowledge/basics-of-logic-gates-and-more?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=last-minute-tutorials-1 Website: https://lmtutorials.com/ Facebook: https://www.facebook.com/Last-Minute-Tutorials-862868223868621/ For any queries or suggestions, kindly mail at: [email protected]
Views: 13224 Last Minute Tutorials
Bridging the Gap Between Data Mining and Machine Learning
 
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Jing Wang, Senior Vice President of Engineering at Baidu, answers a question about the company's challenge of not having the ability to process all of the data that it collects. Wang believes that much of this gap can be closed as advances in machine learning are made. Wang spoke on the panel "'Made in China' Innovation" at the China 2.0 Forum in Beijing hosted by Stanford Graduate School of Business on April 11, 2014. The panel was moderated by Marguerite Gong Hancock of Stanford Graduate School of Business and also featured Hurst Lin, General Partner at DCM China. Learn more about the 2014 China 2.0 Forum: http://sprie.gsb.stanford.edu/docs/2014_china20_forum. China 2.0 is an initiative of the Stanford Graduate School of Business focusing on innovation and entrepreneurship in China. Learn more: http://gsb.stanford.edu/China2.0
Data Mining & Business Intelligence | Tutorial #1 | The KDD Process
 
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Order my books at 👉 http://www.tek97.com/ Understand the process of extracting knowledge from the facts listed under the KDD. There are 7 different steps to follow it. Watch it now! Comprender el proceso de extraer conocimiento de los hechos enumerados bajo el KDD. Hay 7 pasos diferentes para seguirlo. ¡Míralo ahora! فهم عملية استخراج المعرفة من الحقائق المدرجة تحت KDD. هناك 7 خطوات مختلفة لمتابعة ذلك. مشاهدته الآن! Verstehen Sie den Prozess der Extraktion von Wissen aus den unter der KDD aufgeführten Fakten. Es gibt 7 verschiedene Schritte, um es zu befolgen. Jetzt ansehen! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2806 Ranji Raj
Meta S. Brown (Keynote): CRISP-DM; The dominant process for data mining
 
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CRISP-DM stands for Cross-Industry Standard Process for Data Mining, is an industry-proven way to guide your data mining efforts. This talk covers this dominant process, what it is, how it is developed, where it is today and why it's time for you to get involved.
Views: 4675 PyData
Data Mining Classification and Prediction ( in Hindi)
 
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A tutorial about classification and prediction in Data Mining .
Views: 19872 Red Apple Tutorials
DM2 Process of Data Mining عمليات التنقيب عن البيانات
 
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أ.محمود رفيق الفرا مختصر مساق التنقيب عن البيانات Data Mining
Views: 4064 MahmoudRFarra
Data Preprocessing
 
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Project Name: Learning by Doing (LBD) based course content development Project Investigator: Prof Sandhya Kode
Views: 31743 Vidya-mitra
Process Mining and Data Science Using ProM
 
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ProM is an extensible framework that supports a wide variety of process mining techniques in the form of plug-ins. It is a must-have tool for data scientists interested in processes. See processmining.org for more information on process mining. Download ProM for free from http://www.promtools.org/.
Views: 6057 P2Mchannel
The Data Science / Data Analytics / CRISP-DM Cycle
 
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I have data lying around. How do I start - and continue - if I want to build a predictive model based on these data? Well, it is not really like following a cooking recipes with precise steps. It is more like adjusting the steps here and there, going back and starting again with different parameters or maybe even more drastically anew with different algorithms. This video explains this general iterative process.
Views: 4620 KNIMETV
Data Mining & Business Intelligence | Tutorial #12 | Data Integration Process
 
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Order my books at 👉 http://www.tek97.com/ Lets see what is Data Integration and its issues in various spheres of Data Mining. Watch now ! لنرى ما هو التكامل البيانات وقضاياها في مختلف مجالات البيانات التنقيب. شاهد الآن ! Давайте посмотрим, что такое Интеграция данных и ее проблемы в различных областях интеллектуального анализа данных. Смотри ! Voyons ce qu'est l'intégration de données et ses problèmes dans diverses sphères de l'exploration de données. Regarde maintenant ! Sehen wir uns an, was Data Integration und ihre Probleme in verschiedenen Bereichen des Data Mining sind. Schau jetzt ! Veamos qué es la integración de datos y sus problemas en varias esferas de la minería de datos. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1228 Ranji Raj
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 224096 Last moment tuitions
Data mining process
 
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An extreme arm of analytics is “predictive analytics” It’s core lies in data mining - which is nothing but a process used to extract usable data from a larger set of any raw data. This technique is heavily used in thousands of tools available today in digital marketing landscape. You have experienced automatic predictions yourself in Flipkart - the way more similar products are shown to you marked as “based on your history”
Views: 45 Saurabh Srivastava
ETL ( Extract Transform Load )   process fully explained  in hindi | Datawarehouse
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 47679 Last moment tuitions
Data Mining with Weka (5.1: The data mining process)
 
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Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 1: The data mining process http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/5DW24X https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 15466 WekaMOOC
Data mining process for collecting Android apps behavior  -  Automatic Training  Mode
 
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Detecting malicious Android applications using Support Vector Machines The purpose of this project is to identify malware (malicious Software)for Android platform using Support Vector Machine (SVM). This SVM, will be able to identify malicious applications before installing on the device and before malware can get any sensitive information. This way our data will be safe from malware. This video shows the basic way for collecting applications behavior data, Data-mining process. This data will be used for training a SVM. For more information : [email protected]
Views: 839 Iker Burguera
016. Process Mining  Data Science in Action - Wil van der Aalst
 
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Современные организации собирают информацию об огромном количестве событий: все действия людей, машин и самой организации записываются. Поэтому в этой сфере так востребована наука о сборе и анализе данных. Но главная задача состоит не в том, чтобы собрать как можно больше информации, а в том, чтобы извлечь из неё то, что поможет оптимизировать бизнес-процессы. Глубинный анализ процессов (Process mining) позволяет исследовать и усовершенствовать бизнес-процессы в организациях и помогает им эффективнее и экономичнее осуществлять свою деятельность. На семинаре вы узнаете подробности использования этого метода от одного из крупнейших специалистов в этой области — Вила Ван Дер Аалста.
To improve Blood Donation Process using Data Mining Techniques | Final Year Projects 2016
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 774 Clickmyproject
What is KNOWLEDGE DISCOVERY? What does KNOWLEDGE DISCOVERY mean? KNOWLEDGE DISCOVERY meaning
 
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What is KNOWLEDGE DISCOVERY? What does KNOWLEDGE DISCOVERY mean? KNOWLEDGE DISCOVERY meaning - KNOWLEDGE DISCOVERY definition - KNOWLEDGE DISCOVERY explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. nowledge discovery describes the process of automatically searching large volumes of data for patterns that can be considered knowledge about the data. It is often described as deriving knowledge from the input data. Knowledge discovery developed out of the data mining domain, and is closely related to it both in terms of methodology and terminology. The most well-known branch of data mining is knowledge discovery, also known as knowledge discovery in databases (KDD). Just as many other forms of knowledge discovery it creates abstractions of the input data. The knowledge obtained through the process may become additional data that can be used for further usage and discovery. Often the outcomes from knowledge discovery are not actionable, actionable knowledge discovery, also known as domain driven data mining, aims to discover and deliver actionable knowledge and insights. Another promising application of knowledge discovery is in the area of software modernization, weakness discovery and compliance which involves understanding existing software artifacts. This process is related to a concept of reverse engineering. Usually the knowledge obtained from existing software is presented in the form of models to which specific queries can be made when necessary. An entity relationship is a frequent format of representing knowledge obtained from existing software. Object Management Group (OMG) developed specification Knowledge Discovery Metamodel (KDM) which defines an ontology for the software assets and their relationships for the purpose of performing knowledge discovery of existing code. Knowledge discovery from existing software systems, also known as software mining is closely related to data mining, since existing software artifacts contain enormous value for risk management and business value, key for the evaluation and evolution of software systems. Instead of mining individual data sets, software mining focuses on metadata, such as process flows (e.g. data flows, control flows, & call maps), architecture, database schemas, and business rules/terms/process.
Views: 1749 The Audiopedia
Coursera Course "Process Mining: Data science in Action"
 
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To register visit https://www.coursera.org/course/procmin About the Course Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action". The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains. Course Syllabus This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments. The course covers the three main types of process mining. The first type of process mining is discovery. A discovery technique takes an event log and produces a process model without using any a-priori information. An example is the Alpha-algorithm that takes an event log and produces a process model (a Petri net) explaining the behavior recorded in the log. The second type of process mining is conformance. Here, an existing process model is compared with an event log of the same process. Conformance checking can be used to check if reality, as recorded in the log, conforms to the model and vice versa. The third type of process mining is enhancement. Here, the idea is to extend or improve an existing process model using information about the actual process recorded in some event log. Whereas conformance checking measures the alignment between model and reality, this third type of process mining aims at changing or extending the a-priori model. An example is the extension of a process model with performance information, e.g., showing bottlenecks. Process mining techniques can be used in an offline, but also online setting. The latter is known as operational support. An example is the detection of non-conformance at the moment the deviation actually takes place. Another example is time prediction for running cases, i.e., given a partially executed case the remaining processing time is estimated based on historic information of similar cases. Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development. The course uses many examples using real-life event logs to illustrate the concepts and algorithms. After taking this course, one is able to run process mining projects and have a good understanding of the Business Process Intelligence field. See To register visit https://www.coursera.org/course/procmin
Views: 8876 P2Mchannel
Introduction to the CRISP DM data mining methodology - webinar recording
 
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When you’re starting out in data mining or predictive analytics it’s all too easy just to jump straight in and hope for the best, but projects approached in this way commonly fail. To maximize your chances of success, you need to apply a structured project management methodology to your data mining plan. The most commonly used such methodology is CRISP DM (cross industry process for data mining). The CRISP DM approach is widely used, robust and well-proven as well as being intuitive and simple to understand. We recommend that all our clients use CRISP DM as the basis of their data mining and predictive analytics projects. Time and again we see that the most successful client projects are those which apply it effectively. Hence, we produced this free webinar which provides a quick introduction to the methodology and some practical advice on how to apply it to your own projects.
Views: 684 Smart Vision Europe
Process Mining with ProM - free online course at FutureLearn.com
 
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Sign up now at http://bit.ly/2rUYp0u 'Process Mining with ProM' is a free online course by Eindhoven University of Technology on FutureLearn.com Process mining is a relatively new and exciting field which combines business process management with data science. Using process mining techniques you can analyse and visualise business processes based on event data recorded in event logs. Process mining provides a critical, process-centric perspective on data, which is not available with classical data mining or machine learning techniques. #FLProM At FutureLearn, we want to inspire learning for life. We offer a diverse selection of free, high quality online courses from some of the world's leading universities and other outstanding cultural institutions. Browse all courses and sign up here: http://www.futurelearn.com
Views: 3726 FutureLearn
Introduction to Data Mining: Data Cleaning
 
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In this video we introduce Data Preprocessing, known as data cleaning, and the different strategies used to tackle it. -- 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/H0f8M6d0 See what our past attendees are saying here: https://hubs.ly/H0f8Ln10 -- 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: 6837 Data Science Dojo
EN: Data mining process in Marketing Miner
 
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How to create a first report in Marketing Miner.
Views: 72 Marketing Miner
What is Datamining | KDD process ?
 
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In this video I discussed about What is Data Mining and the process of Knowledge Discovery in Databases(KDD). Data mining is the process of discovering interesting patterns and knowledge from Huge amounts of data. The steps of KDD Process are : Data cleaning Data integration Data selection Data transformation Data mining Pattern evaluation Knowledge presentation
Views: 1985 DataMining Tutorials
Data Mining & Business Intelligence | Tutorial #13 | Data Transformation Process
 
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Order my books at 👉 http://www.tek97.com/ Interested to know about how data is transformed in Data Mining well this video is the answer for that! Watch now ! مهتم بمعرفة كيف يتم تحويل البيانات في Data Mining بشكل جيد هذا الفيديو هو الحل لذلك! شاهد الآن ! Interesado en saber cómo se transforman los datos en Data Mining, este video es la respuesta para eso. Ver ahora ! Interessiert zu wissen, wie Daten in Data Mining umgewandelt werden, ist dieses Video die Antwort dafür! Schau jetzt ! Intéressé de savoir comment les données sont transformées dans Data Mining bien cette vidéo est la réponse pour cela! Regarde maintenant ! Заинтересованы в том, как данные преобразуются в Data Mining, и это видео является ответом на это! Смотри ! Interesado en saber cómo se transforman los datos en Data Mining, este video es la respuesta para eso. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 939 Ranji Raj
productronica 2017 - Process Optimizing through Data Mining and Machine Learning
 
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Florian Schwarz: "A warm welcome to productronica 2017. The special shows here are a big highlight – because that's where you can experience electronics manufacturing live!" "Founded in April 2017: the research fab Microelectronics Germany. This is where research capacities all over the country are bundled together and connected, to give the fab more weight internationally as a centre for microelectronics."   "Ah, Dr. Olowinsky. Hello!"    "Laser microwelding. What exactly are we looking at here?"   Dr. Alexander Olowinsky: "Laser microwelding is an established method in electronics and precision engineering for creating electrical and mechanical connections.Here you can see a laser beam melting material – and that's what creates the connection. In this particular version, the laser head contains the beam guidance, beam forming and mechanical pressing combined, for a flexible manufacturing process."   Florian Schwarz: "And what are the areas of application?"   Dr. Alexander Olowinsky: "What you see here: classic battery technology, production of battery modules and of battery packs, production of electrical connections,all the way to printed circuit board technology, because we need to create connections there too."   Florian Schwarz: "Dr. Olowinsky, thanks a lot!" Florian Schwarz: "From microelectronics to the special show devoted to hardware data mining.With me now is Ulf Oestermann, business developer at Fraunhofer IZM.Good morning!"   FlorianSchwarz: "Mr. Oestermann, what's the connection between microelectronics and hardware data mining?"   Ulf Oestermann: "The research fab Microelectronics Germany supposed to develop technologies and processes for the future. And they then have to be ported into mass production and scaled, so that they're ready to use there. That's exactly what hardware data mining is all about – showing what data records accumulate at what location in the individual process steps, and how robust they have to be in order to be used."   Florian Schwarz: "So we're talking about 'digging' data? Can we take a closer look?"   Ulf Oestermann: "Sure. No problem."   Ulf Oestermann: "Based on the data matrix code, you can immediately establish when this subassembly was manufactured, at what temperature, and in what humidity, and then conclusions can be drawn about possible errors."   Florian Schwarz: "I guess it helps save on resources – only having to replace individual components?"   Ulf Oestermann: "It's showing how thick wire is bonded. A very, very large number of wires are needed to get a high current density in the contact."   Florian Schwarz: "Mr. Oestermann, thanks very much for the tour. Hardware data mining. I'm going to the VDMA now to see what's being done with the data. And you? Back to work?"   Ulf Oestermann: "That's right!"   Florian Schwarz: "Ok - thanks. Ciao! We've just mined and collected the data. The data has to go somewhere, it has to be processed. And that brings me to the special show of the VDMA: "Smart-Data-Future Manufacturing."   "With me now is Mr. Müller from the VDMA. I've just taken a look round your stand. There's a lot of data being generated here. What's going to be done with it?"    Daniel Müller: "In the next stage, it's simply stored in various cloud systems, to make the long-term data actually usable. For models, for instance – like predictive maintenance."   Florian Schwarz: "Smart Data. How do you see the future of that?"   Daniel Müller: "A very exciting future topic is machinelearning - where companies try to make machines learn. So they can avoid errors, or correct them, all by themselves."   Florian Schwarz: "Wow. Thank you very much, Mr. Müller! Smart Data Future Manufacturing – it's a topic we're going to keep a close eye on. Well, that's all from productronica 2017. I'm already looking forward to 2019! Goodbye!"
Views: 311 productronica
Introduction to Event Log Mining with R
 
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Event logs are everywhere and represent a prime source of Big Data. Event log sources run the gamut from e-commerce web servers to devices participating in globally distributed Internet of Things (IoT) architectures. Even Enterprise Resource Planning (ERP) systems produce event logs! Given the rich and varied data contained in event logs, mining these assets is a critical skill needed by every Data Scientist, Business/Data Analyst, and Program/Product Manager. At this meetup, presenter Dave Langer, will show how easy it is to get started mining your event logs using the OSS tools of R and ProM. Dave will cover the following during the presentation: • The scenarios and benefits of event log mining • The minimum data required for event log mining • Ingesting and analyzing event log data using R • Process Mining with ProM • Event log mining techniques to create features suitable for Machine Learning models • Where you can learn more about this very handy set of tools and techniques *R source code will be made available via GitHub here: https://github.com/EasyD/IntroToEventLogMiningMeetup Find out more about David here: https://www.meetup.com/data-science-dojo/events/235913034/ -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8y2K0 See what our past attendees are saying here: https://hubs.ly/H0f8xNz0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 5654 Data Science Dojo
Binning | Binning Method | Binning Algorithm | Binning In Data Mining
 
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Binning |Binning Method | Binning Algorithm | Binning In Data Mining ************************************************ the binding of isaac, binning , binnington, equal width binning, binning method, binning algorithm, bin data in r, bin data in excel, binning in excel, binning in data mining, data mining, data mining techniques, data mining tutorial, data mining algorithms, data mining course, data mining excel, r data minin, python data mining, Please Subscribe My Channel
Views: 10369 Learning With Mahamud

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