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The Model Driven Approach for Data Integration, by Stambia
 
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This short video explains how Stambia can provide agility and flexibility through a Model Driven Approach of Data Integration.
Views: 319 Stambia
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
01:38:50
***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 140433 edureka!
Introduction to data mining and architecture  in hindi
 
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Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 For full course:https://goo.gl/bYbuZ2 More videos coming soon so Subscribe karke rakho  :  https://goo.gl/85HQGm for full notes   please fill the form for notes :https://goo.gl/forms/MJD1mAOaTzyag64P2 For full hand made  notes of data warehouse and data mining  its only 200rs payment options is PAYTM :7038604912 once we get payment notification we will mail you the notes on your email id contact us at :[email protected] For full course :https://goo.gl/Y1UcLd Topic wise: Introduction to Datawarehouse:https://goo.gl/7BnSFo Meta data in 5 mins :https://goo.gl/7aectS Datamart in datawarehouse :https://goo.gl/rzE7SJ Architecture of datawarehouse:https://goo.gl/DngTu7 how to draw star schema slowflake schema and fact constelation:https://goo.gl/94HsDT what is Olap operation :https://goo.gl/RYQEuN OLAP vs OLTP:https://goo.gl/hYL2kd decision tree with solved example:https://goo.gl/nNTFJ3 K mean clustering algorithm:https://goo.gl/9gGGu5 Introduction to data mining and architecture:https://goo.gl/8dUADv Naive bayes classifier:https://goo.gl/jVUNyc Apriori Algorithm:https://goo.gl/eY6Kbx Agglomerative clustering algorithmn:https://goo.gl/8ktMss KDD in data mining :https://goo.gl/K2vvuJ ETL process:https://goo.gl/bKnac9 FP TREE Algorithm:https://goo.gl/W24ZRF Decision tree:https://goo.gl/o3xHgo more videos coming soon so channel ko subscribe karke rakho
Views: 126687 Last moment tuitions
INTRODUCTION TO DATA MINING IN HINDI
 
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find relevant notes at-https://viden.io/
Views: 96243 LearnEveryone
Excel and DataTables Automation 3.3
 
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Learn how UiPath operates with Excel and Data Tables: - Excel application scope - Opening a workbook - access modes - Read and write range - Output datatable Watch a practical example of how to sort data in an Excel file and iterate through all rows.
Views: 142852 UiPath
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.
Generating Reports from Model Data
 
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In this webinar, you will learn how to create custom report templates in Cameo Systems Modeler/MagicDraw. This Session Demonstrates: - Creating templates for Microsoft® Word, Excel, and PowerPoint - Creating XML templates for interchanging data between modeling tools - Using VTL in combination with scripts to develop advanced templates The session is hosted by Edgaras Dulskis, Developer at No Magic Europe.
Views: 1262 No Magic
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 79140 StudyYaar.com
Interview with a Data Analyst
 
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This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 258486 Udacity
How to link PowerPoint to Excel for dynamic data updates?
 
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Sometimes you want to display live information in a PowerPoint presentation. Maybe you need to display scores or results in real time to people on a television screen. A manager needs to see production figures of a factory at his desk. People on the floor need to know their targets etc. This can be accomplished with data driven presentations. To display numbers and figures you don’t use a word processor but a spreadsheet like Microsoft Excel. There you can enter your raw data and make some simple or complex calculations. Of course you don’t want to display an Excel sheet on your message boards with its grid lines etc but you need presentation software like Microsoft PowerPoint. PowerPoint is the ideal software for presentations but it is static. There is a tool DataPoint available that allows you to create dynamic presentations with live data from Excel worksheets. Some people tend to copy and paste Excel objects in their PowerPoint but that is not done. It will even not update automatically over the network. You see the Excel grid lines in a presentation which is not professional looking. You can use the data only from the Excel worksheet but you do the formatting in your PowerPoint presentation. You can emphasize which text boxes are more important by setting a color, or a more important position on the slide with maybe arrows pointing to this value and some animation. PowerPoint, with its data from Excel, gives you more control! Let me show you how easily you can display live information from an Excel worksheet in a PowerPoint and update in real time. -------------------------------------------------------------- Download Free PowerPoint Digital Signage and other templates here: https://www.presentationpoint.com/templates/ Access our Free online course: "How to Use PowerPoint for Digital Signage" http://presentationpoint.usefedora.com/courses/how-to-use-powerpoint-for-digital-signage -------------------------------------------------------------- Connect with us on Social: Facebook: https://www.facebook.com/PresentationPoint Twitter: https://twitter.com/PresentationPnt YouTube: https://www.youtube.com/c/PresentationPointChannel LinkedIn: http://www.linkedin.com/company/3500848 Google+: https://plus.google.com/+Presentationpoint
Views: 79884 PresentationPoint
MicroStrategy - Microsoft Office Integration - Online Training Video by MicroRooster
 
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Source: MicroRooster.blogspot.com Twitter: @MicroRooster Format: A MicroStrategy Online Training Video blog. Description: This short video show users how to use Microsoft tools such as Excel with MicroStrategy. A seamless integration with powerful results.
Views: 2484 MicroRooster
Introduction to Datawarehouse in hindi
 
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Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 For full course:https://goo.gl/bYbuZ2 More videos coming soon so Subscribe karke rakho  :  https://goo.gl/85HQGm for full notes   please fill the form for notes :https://goo.gl/forms/MJD1mAOaTzyag64P2 For full hand made  notes of data warehouse and data mining  its only 200 rs payment options is PAYTM :7038604912 once we get payment notification we will mail you the notes on your email id contact us at :[email protected] For full course :https://goo.gl/Y1UcLd Topic wise: Introduction to Datawarehouse:https://goo.gl/7BnSFo Meta data in 5 mins :https://goo.gl/7aectS Datamart in datawarehouse :https://goo.gl/rzE7SJ Architecture of datawarehouse:https://goo.gl/DngTu7 how to draw star schema slowflake schema and fact constelation:https://goo.gl/94HsDT what is Olap operation :https://goo.gl/RYQEuN OLAP vs OLTP:https://goo.gl/hYL2kd decision tree with solved example:https://goo.gl/nNTFJ3 K mean clustering algorithm:https://goo.gl/9gGGu5 Introduction to data mining and architecture:https://goo.gl/8dUADv Naive bayes classifier:https://goo.gl/jVUNyc Apriori Algorithm:https://goo.gl/eY6Kbx Agglomerative clustering algorithmn:https://goo.gl/8ktMss KDD in data mining :https://goo.gl/K2vvuJ ETL process:https://goo.gl/bKnac9 FP TREE Algorithm:https://goo.gl/W24ZRF Decision tree:https://goo.gl/o3xHgo more videos coming soon so channel ko subscribe karke rakho
Views: 191020 Last moment tuitions
What is Big Data? in Tamil | The Future is Here | #Visaipalagai
 
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Have you heard about the term BIG DATA? So here is the video about big data explained in Tamil Language! You can make use of the comments below to ask any questions regarding BIG DATA...........Big Data - The Future is Here ! Playlists: Best Apps - https://goo.gl/oyFHt0 Tech Guide - https://goo.gl/6EOVEz Explained - https://goo.gl/zYTvZ7 Social Media Links: Facebook Page: https://goo.gl/H7rfHW Twitter - https://goo.gl/3Rzg6A Instagram - https://goo.gl/OmI2uM ALL QUALITY TECH VIDEOS - தமிழில் by Ranjeth Kumar VISAIPALAGAI - தமிழ் #AskRanjethvisai Music Credit: www.bensound.com Footage Credit: www.videvo.net
Views: 21849 Visaipalagai
How kNN algorithm works
 
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In this video I describe how the k Nearest Neighbors algorithm works, and provide a simple example using 2-dimensional data and k = 3.
Views: 327941 Thales Sehn Körting
Principal Components Analysis - Georgia Tech - Machine Learning
 
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Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-649069103/m-661438544 Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262 Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Views: 225750 Udacity
Data Mining using R | R Tutorial for Beginners | Data Mining Tutorial for Beginners 2018 | ExcleR
 
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Data Mining Using R (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. Data Mining Certification Training Course Content : https://www.excelr.com/data-mining/ Introduction to Data Mining Tutorials : https://youtu.be/uNrg8ep_sEI What is Data Mining? Big data!!! Are you demotivated when your peers are discussing about data science and recent advances in big data. Did you ever think how Flip kart and Amazon are suggesting products for their customers? Do you know how financial institutions/retailers are using big data to transform themselves in to next generation enterprises? Do you want to be part of the world class next generation organisations to change the game rules of the strategy making and to zoom your career to newer heights? Here is the power of data science in the form of Data mining concepts which are considered most powerful techniques in big data analytics. Data Mining with R unveils underlying amazing patterns, wonderful insights which go unnoticed otherwise, from the large amounts of data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, unbiased and scientific-driven decisions. Data mining has powerful tools and techniques that answer business questions in a scientific manner, which traditional methods cannot answer. Adoption of data mining concepts in decision making changed the companies, the way they operate the business and improved revenues significantly. Companies in a wide range of industries such as Information Technology, Retail, Telecommunication, Oil and Gas, Finance, Health care are already using data mining tools and techniques to take advantage of historical data and to create their future business strategies. Data mining can be broadly categorized into two branches i.e. supervised learning and unsupervised learning. Unsupervised learning deals with identifying significant facts, relationships, hidden patterns, trends and anomalies. Clustering, Principle Component Analysis, Association Rules, etc., are considered unsupervised learning. Supervised learning deals with prediction and classification of the data with machine learning algorithms. Weka is most popular tool for supervised learning. Topics You Will Learn… Unsupervised learning: Introduction to datamining Dimension reduction techniques Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Association rules / Market Basket Analysis / Affinity Filtering Recommender Systems / Recommendation Engine / Collaborative Filtering Network Analytics – Degree centrality, Closeness Centrality, Betweenness Centrality, etc. Cluster Analysis Hierarchical clustering K-means clustering Supervised learning: Overview of machine learning / supervised learning Data exploration methods Basic classification algorithms Decision trees classifier Random Forest K-Nearest Neighbours Bayesian classifiers: Naïve Bayes and other discriminant classifiers Perceptron and Logistic regression Neural networks Advanced classification algorithms Bayesian Networks Support Vector machines Model validation and interpretation Multi class classification problem Bagging (Random Forest) and Boosting (Gradient Boosted Decision Trees) Regression analysis Tools You Will Learn… R: R is a programming language to carry out complex statistical computations and data visualization. R is also open source software and backed by large community all over the world who are contributing to enhancing the capability. R has many advantages over other tools available in the market and it has been rated No.1 among the data scientist community. Mode of Trainings : E-Learning Online Training ClassRoom Training --------------------------------------------------------------------------- For More Info Contact :: Toll Free (IND) : 1800 212 2120 | +91 80080 09704 Malaysia: 60 11 3799 1378 USA: 001-608-218-3798 UK: 0044 203 514 6638 AUS: 006 128 520-3240 Email: [email protected] Web: www.excelr.com
Mining Structured and Unstructured Data
 
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Oracle Advanced Analytics (OAA) Database Option leverages Oracle Text, a free feature of the Oracle Database, to pre-process (tokenize) unstructured data for ingestion by the OAA data mining algorithms. By moving, parallelized implementations of machine learning algorithms inside the Oracle Database, data movement is eliminated and we can leverage other strengths of the Database such as Oracle Text (not to mention security, scalability, auditing, encryption, back up, high availability, geospatial data, etc.. This YouTube video presents an overview of the capabilities for combing and data mining structured and unstructured data, includes several brief demonstrations and instructions on how to get started--either on premise or on the Oracle Cloud.
Views: 2058 Charlie Berger
Data Preprocessing
 
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Project Name: Learning by Doing (LBD) based course content development Project Investigator: Prof Sandhya Kode
Views: 29074 Vidya-mitra
Data Warehouse Interview Questions And Answers | Data Warehouse Tutorial | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Interview Questions And Answers tutorial will help you prepare for Data Warehouse interviews. Watch the entire video to get an idea of the 30 most frequently asked questions in Data Warehouse interviews. - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehouseInterviewQuestions #DataWarehouseConcepts #DataWarehouseTutorial Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 58866 edureka!
E-commerce data integration through nature-inspired algorithms
 
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This video describes e-commerce data integration problems and how nature-inspired algorithms can contribute to address them. This video is submitted to the Webinar Competition 2015 supported by IEEE CIS.
Views: 384 Autilia Vitiello
How To Install KNIME Analytics Platform on Windows, Installation and Administration Guide
 
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This video is an introduction of KNIME. KNIME is an open source platform for data analysis, predictive KNIME, the open platform for your data. ... Course for KNIME Analytics Platform, Berlin - November 2017. 15 Nov 2017. Course for KNIME Server, Berlin KNIME (pronounced /naɪm/), the Konstanz Information Miner, is an open source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface allows assembly of nodes for data preprocessing (ETL: Extraction, Transformation, Loading), for modeling and data analysis and visualization without, or with only minimal, programming. To some extent KNIME can be considered as an SAS alternative. Since 2006, KNIME has been used in pharmaceutical research,[2] but is also used in other areas like CRM customer data analysis, business intelligence and financial data analysis. History: The Development of KNIME was started January 2004 by a team of software engineers at University of Konstanz as a proprietary product. The original developer team headed by Michael Berthold came from a company in Silicon Valley providing software for the pharmaceutical industry. The initial goal was to create a modular, highly scalable and open data processing platform which allowed for the easy integration of different data loading, processing, transformation, analysis and visual exploration modules without the focus on any particular application area. The platform was intended to be a collaboration and research platform and should also serve as an integration platform for various other data analysis projects. In 2006 the first version of KNIME was released and several pharmaceutical companies started using KNIME and a number of life science software vendors began integrating their tools into KNIME. Later that year, after an article in the German magazine c't users from a number of other areas[9][10] joined ship. As of 2012, KNIME is in use by over 15,000 actual users (i.e. not counting downloads but users regularly retrieving updates when they become available) not only in the life sciences but also at banks, publishers, car manufacturer, telcos, consulting firms, and various other industries but also at a large number of research groups worldwide. Latest updates to KNIME Server and KNIME Big Data Extensions, provide support for Apache Spark 2.0. Internals KNIME allows users to visually create data flows (or pipelines), selectively execute some or all analysis steps, and later inspect the results, models, and interactive views. KNIME is written in Java and based on Eclipse and makes use of its extension mechanism to add plugins providing additional functionality. The core version already includes hundreds of modules for data integration (file I/O, database nodes supporting all common database management systems through JDBC), data transformation (filter, converter, combiner) as well as the commonly used methods of statistics, data mining, analysis and text analytics. Visualization supports with the free Report Designer extension. KNIME workflows can be used as data sets to create report templates that can be exported to document formats like doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (most other open source data analysis tools work in main memory and are therefore limited to the available RAM). E.g. KNIME allows analysis of 300 million customer addresses, 20 million cell images and 10 million molecular structures. Additional plugins allows the integration of methods for Text mining, Image mining, as well as time series analysis. KNIME integrates various other open-source projects, e.g. machine learning algorithms from Weka, the statistics package R project, as well as LIBSVM, JFreeChart, ImageJ, and the Chemistry Development Kit. KNIME is implemented in Java but also allows for wrappers calling other code in addition to providing nodes that allow running Java, Python, Perl and other code fragments. also a ML tool is WEKA(A Data Mining Tool)
Views: 115 Hammad Zafar
Data Integration Infographic Video
 
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Data Integration is one of the UK's leading networking, security and communication technology providers, serving more than 300 customers in the UK, spanning the private and public sectors.
Views: 804 DataIntegrationUK
Data Preprocessing Steps for Machine Learning & Data analytics
 
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#Pandas #DataPreProcessing #MachineLearning #DataAnalytics #DataScience Data Preprocessing is an important factor in deciding the accuracy of your Machine Learning model. In this tutorial, we learn why Feature Selection , Feature Extraction, Dimentionality Reduction are important. We also learn about the famous methods which can be used for the purpose. Data Preprocessing is a very important step in Data Analytics which is ignored by many. To make your models accurate you have to ensure proper preprocessing as the Machine Learning model is highly dependent on data. For all Ipython notebooks, used in this series : https://github.com/shreyans29/thesemicolon Facebook : https://www.facebook.com/thesemicolon.code Support us on Patreon : https://www.patreon.com/thesemicolon Python for Data Analysis book : http://amzn.to/2oDief8 Pattern Recognition and Machine Learning : http://amzn.to/2p6mD6R
Views: 6987 The SemiColon
Seadrill are mining the benefits of Azure big data.
 
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Seadrill are revolutionising how data is collected, visualised and utilised in the deep-water drilling industry.
Views: 1590 Microsoft UK
Understanding Wavelets, Part 1: What Are Wavelets
 
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This introductory video covers what wavelets are and how you can use them to explore your data in MATLAB®. •Try Wavelet Toolbox: https://goo.gl/m0ms9d •Ready to Buy: https://goo.gl/sMfoDr The video focuses on two important wavelet transform concepts: scaling and shifting. The concepts can be applied to 2D data such as images. Video Transcript: Hello, everyone. In this introductory session, I will cover some basic wavelet concepts. I will be primarily using a 1-D example, but the same concepts can be applied to images, as well. First, let's review what a wavelet is. Real world data or signals frequently exhibit slowly changing trends or oscillations punctuated with transients. On the other hand, images have smooth regions interrupted by edges or abrupt changes in contrast. These abrupt changes are often the most interesting parts of the data, both perceptually and in terms of the information they provide. The Fourier transform is a powerful tool for data analysis. However, it does not represent abrupt changes efficiently. The reason for this is that the Fourier transform represents data as sum of sine waves, which are not localized in time or space. These sine waves oscillate forever. Therefore, to accurately analyze signals and images that have abrupt changes, we need to use a new class of functions that are well localized in time and frequency: This brings us to the topic of Wavelets. A wavelet is a rapidly decaying, wave-like oscillation that has zero mean. Unlike sinusoids, which extend to infinity, a wavelet exists for a finite duration. Wavelets come in different sizes and shapes. Here are some of the well-known ones. The availability of a wide range of wavelets is a key strength of wavelet analysis. To choose the right wavelet, you'll need to consider the application you'll use it for. We will discuss this in more detail in a subsequent session. For now, let's focus on two important wavelet transform concepts: scaling and shifting. Let' start with scaling. Say you have a signal PSI(t). Scaling refers to the process of stretching or shrinking the signal in time, which can be expressed using this equation [on screen]. S is the scaling factor, which is a positive value and corresponds to how much a signal is scaled in time. The scale factor is inversely proportional to frequency. For example, scaling a sine wave by 2 results in reducing its original frequency by half or by an octave. For a wavelet, there is a reciprocal relationship between scale and frequency with a constant of proportionality. This constant of proportionality is called the "center frequency" of the wavelet. This is because, unlike the sinewave, the wavelet has a band pass characteristic in the frequency domain. Mathematically, the equivalent frequency is defined using this equation [on screen], where Cf is center frequency of the wavelet, s is the wavelet scale, and delta t is the sampling interval. Therefore when you scale a wavelet by a factor of 2, it results in reducing the equivalent frequency by an octave. For instance, here is how a sym4 wavelet with center frequency 0.71 Hz corresponds to a sine wave of same frequency. A larger scale factor results in a stretched wavelet, which corresponds to a lower frequency. A smaller scale factor results in a shrunken wavelet, which corresponds to a high frequency. A stretched wavelet helps in capturing the slowly varying changes in a signal while a compressed wavelet helps in capturing abrupt changes. You can construct different scales that inversely correspond the equivalent frequencies, as mentioned earlier. Next, we'll discuss shifting. Shifting a wavelet simply means delaying or advancing the onset of the wavelet along the length of the signal. A shifted wavelet represented using this notation [on screen] means that the wavelet is shifted and centered at k. We need to shift the wavelet to align with the feature we are looking for in a signal.The two major transforms in wavelet analysis are Continuous and Discrete Wavelet Transforms. These transforms differ based on how the wavelets are scaled and shifted. More on this in the next session. But for now, you've got the basic concepts behind wavelets.
Views: 120546 MATLAB
How to export Tableau Dashboard images to PPT
 
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Learn how to export Tableau Dashboard images to PowerPoint Presentation using RapidDox.
Views: 20689 Factual Soft
Data Warehouse Concepts | Data Warehouse Tutorial | Data Warehouse Architecture | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This tutorial on data warehouse concepts will tell you everything you need to know in performing data warehousing and business intelligence. The various data warehouse concepts explained in this video are: 1. What Is Data Warehousing? 2. Data Warehousing Concepts: 3. OLAP (On-Line Analytical Processing) 4. Types Of OLAP Cubes 5. Dimensions, Facts & Measures 6. Data Warehouse Schema - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining #DataWarehouseConcepts Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 34223 edureka!
DWM -  Benefits and Users of Data Warehouse
 
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In this video, we cover the following topics- 1. Benefits of Data Warehouse 2. Users of Data Warehouse Link of previous video- https://youtu.be/556RfSpK5Qk Tutorial lecture by Anisha Lalwani
Views: 369 topNotch Tutorials
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI Training Video | Edureka
 
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This Edureka SSIS Tutorial video will help you learn the basics of MSBI. SSIS is a platform for data integration and workflow applications. This video covers data warehousing concepts which is used for data extraction, transformation and loading (ETL). It is ideal for both beginners and professionals who want to brush up their basics of MSBI. This Edureka training video provides knowledge on the following topics: 1. Why do we need data integration? 2. What is data integration? 3. Why SSIS? 4. What is SSIS? 5. ETL process 6. Data Warehousing 7. Installation 8. What is SSIS Package? 9. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Microsoft BI playlist here: https://goo.gl/Vo6Klo #SSIS #SSISTutorial #MicrosoftBI #MicrosoftBItutorial #MicrosoftBIcourse How it Works? 1. This is a 30 Hours of Online Live Instructor-Led Classes. Weekend Class : 10 sessions of 3 hours each. Weekday Class : 15 sessions of 2 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Microsoft BI Certification Course is designed to provide insights on different tools in Microsoft BI Suite (SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services). Get expertise in SSIS , SSAS & SSRS concepts and master them. The course will give you the practical knowledge on Data Warehouse concepts and how these tools help in developing a robust end-to-end BI solution using the Microsoft BI Suite. Who should go for this course? Microsoft BI Certification Course at Edureka is designed for professionals aspiring to make a career in Business Intelligence. Software or Analytics professionals having background/experience of any RDBMS, ETL, OLAP or reporting tools are the key beneficiaries of this MSBI course. You can check a blog related to Microsoft BI – Why You Need It For A Better Business Intelligence Career!! Also, once your Microsoft BI training is over, you can check the Microsoft Business Intelligence Interview Questions related edureka blog. Why learn Microsoft BI ? As we move from experience and intuition based decision making to actual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end to end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses. Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Website: https://www.edureka.co/microsoft-bi Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Amit Vij, HRSSC HRIS Senior Advisor at DLA Piper, says "I am not a big fan of online courses and also opted for class room based training sessions in past. Out of surprise, I had a WoW factor when I attended first session of my MSBI course with Edureka. Presentation - Check, Faculty - Check, Voice Clarity - Check, Course Content - Check, Course Schedule and Breaks - Check, Revisting Past Modules - Awesome with a big check. I like the way classes were organised and faculty was far above beyond expectations. I will recommend Edureka to everyone and will personally revisit them for my future learnings."
Views: 81190 edureka!
Lesson 5 Basic Python for Data Analytics Social Media & Twitter Analysis
 
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The objective of this channel is to give you an overview of pandas in analytics for business practitioners especially as Marketing/ Social Media Analyst tapping on big data: pandas is a DataFrame Framework, a library that stores data in a highly efficient spreadsheet format and functions. Efficient in: Data Structure (numpy) Computing time (since DataFrame is processed by C++, it runs in a well streamlined computing environment) Highly optimized and updated processes And I will end the sharing with some planned resources to help you learn analytics in the future. Feel free to access my github for Twitter Social Media Analysis (http://bit.ly/2koxDdZ) This is the playlist where I am going to explain step by step of this tutorial (https://youtu.be/YnMhFV8Q_K4) Hopefully by the end of this video you could be more inspired to learn analytics and follow through the journey Feel free to open my repository(contains powerpoint slides at): https://drive.google.com/drive/folders/0B7MOgjR94z_veUdHVGV4aENZSkk
Views: 1234 Vincent Tatan
9 Discretization
 
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Views: 330 RAJESH KUMAR
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 409622 Brandon Weinberg
What is Data Mining?
 
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NJIT School of Management professor Stephan P Kudyba describes what data mining is and how it is being used in the business world.
Views: 346667 YouTube NJIT
A Survey on Trajectory Data Mining: Techniques Applications | Final Year Projects 2016 - 2017
 
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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/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 269 ClickMyProject
Presentation Data Mining & Decision-making: Case of Amazon.com
 
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Week 2 assignment for MooreFMIS7003 course at NCU. Prepared by FahmeenaOdetta Moore.
Data Mining & Business Intelligence | Tutorial #8 | Data Summarization Techniques
 
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Order my books at 👉 http://www.tek97.com/ This video addresses the data summarization techniques in data mining which are most frequently used! Watch now ! يتناول هذا الفيديو تقنيات تلخيص البيانات في مجال استخراج البيانات الأكثر استخدامًا! شاهد الآن ! Este video aborda las técnicas de resumen de datos en la minería de datos que se utilizan con mayor frecuencia. Ver ahora ! В этом видео чаще всего используются методы обобщения данных в области интеллектуального анализа данных! Смотри ! In diesem Video werden die am häufigsten verwendeten Datenzusammenfassungstechniken im Data Mining behandelt! 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: 334 Ranji Raj
Sampling: Simple Random, Convenience, systematic, cluster, stratified - Statistics Help
 
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This video describes five common methods of sampling in data collection. Each has a helpful diagrammatic representation. You might like to read my blog: https://creativemaths.net/blog/
Views: 617000 Dr Nic's Maths and Stats
Lecture 48 — Dimensionality Reduction with SVD | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Introducing The Business Data Analysis with Excel and Power BI Course
 
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The Business Data Analysis with Excel and Power BI Course on Udemy at https://www.udemy.com/business-data-analysis-with-microsoft-excel/ You can also register for our in-class training at https://www.urbizedge.com/Excel
Views: 4764 Michael Olafusi
Talend Tutorial for Beginners - 1 | Talend ETL Tutorial - 1 | Edureka
 
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( Talend Training - https://www.edureka.co/talend-for-big-data ) Updated Talend Tutorial Video : https://goo.gl/PPH2cz Talend simplifies the integration of big data so you can respond to business demands without having to write or maintain complicated Apache Hadoop code. Enable existing developers to start working with Hadoop and NoSQL databases today. Use simple, graphical tools and wizards to generate native code that leverages the full power of Hadoop and accelerates your path to informed decisions. Video gives a brief insight of following topics: 1.What is ETL? 2.Learn how to adopt ETL to big data industry 3.Learn Big Data in minutes 4.Use cases of Talend 5.Implementing Talend job with Hadoop 6.Why Talend ? 7.Integrating Talend and Hadoop Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world. The topics related to Talend have extensively been covered in our course 'Talend For Big Data’. For more information, please write back to us at [email protected] Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 136019 edureka!
Data Mining Tool: extra features
 
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Some extra features of the Data Mining Tool. Heatmaps and Gene Set Enrichment.
Views: 59 QMRIBioinf
Data pre processing – 1 Summarization and Cleaning Methods
 
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Project Name: e-Content generation and delivery management for student –Centric learning Project Investigator:Prof. D V L N Somayajulu
Views: 4726 Vidya-mitra
Anomaly Detection: Algorithms, Explanations, Applications
 
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Anomaly detection is important for data cleaning, cybersecurity, and robust AI systems. This talk will review recent work in our group on (a) benchmarking existing algorithms, (b) developing a theoretical understanding of their behavior, (c) explaining anomaly "alarms" to a data analyst, and (d) interactively re-ranking candidate anomalies in response to analyst feedback. Then the talk will describe two applications: (a) detecting and diagnosing sensor failures in weather networks and (b) open category detection in supervised learning. See more at https://www.microsoft.com/en-us/research/video/anomaly-detection-algorithms-explanations-applications/
Views: 4536 Microsoft Research
Human resources, CRM, data mining and social media concept - officer looking for employee represente
 
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To download this template in PowerPoint format (.pptx) please go to link below: http://www.smiletemplates.com/powerpoint-templates/human-resources-crm-data-mining-and-social-media-concept-officer-looking-for-employee-represente/09570/ If you want see some related templates on these theme, please go to: http://www.smiletemplates.com/search/powerpoint-templates/professional/0.html
1 - Introduction to Data warehouse and Data warehousing
 
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Short Introduction Video to understand, What is Data warehouse and Data warehousing? How it is different from Database? It also talks about properties of Data warehouse which are Subject Oriented, Integrated, Time Variant, Non Volatile ETL Tools: Talend Open Studio, Jaspersoft ETL, Ab initio, Informatica, Datastage, Clover ETL, Pentaho ETL, Kettle. #datawarehouse #ETL #DWH Business Intelligence tools: Oracle BI, Microsoft BI suite, Tableau, Qlik, Jaspersoft BI, Pentabo BI, Miscrostrategy, Tibco For more details visit: http://www.vikramtakkar.com/2015/08/what-is-datawarehouse-and.html Datawarehouse Playlist: https://www.youtube.com/playlist?list=PLJ4bGndMaa8FV7nrvKXeHCLRMmIXVCyOG
Views: 91990 Vikram Takkar
Data Integrity in Pharma
 
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Data integrity in the pharmaceutical industry is a challenge. Not only deliberate counterfeiting, but also carelessness or technical errors can lead to violations and thus to poor audit results. What you should consider to pass a data integrity audit. Learn more at: https://www.hgp.ag/services/data-integrity/
Design of Medical Data Monitoring by Using Raspberry Pi3 and LABVIEW - part2
 
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1. Design of Medical Data Monitoring by Using Raspberry Pi.The cost of the project is 12500/-. 2. Raspberry Pi Based Patient Monitoring System using Wireless - IRJET, 3. An IoT Based Patient Monitoring System using Raspberry Pi, 4. Raspberry Pi Based Wearable RFID Tag Design for Medical Care - ijitr, 5. A Review on system of IOT Based Human Activity Monitoring By Using Raspberry Pi, 6. Real Time Vehicle Tracking And Monitoring Using Raspberry Pi, 7. IoT Based Air Quality Monitoring System Using Raspberry-PI, 8. E Health Sensor Platform For Arduino and Raspberry Pi Biometric, 9. Sensor Technologies: Healthcare, Wellness - UW Moodle Fall 2014, 10. Implementation of Tcp/Ip on Embedded Webserver Using Raspberry, 11. Wearable Internet of Things - from Human Activity Tracking to Clinical, 12. INDUSTRIAL AUTOMATION AND SURVEILLANCE USING - IJRIER, 13. A Cloud-Based Internet of Things Platform for Raspberry P - BioMedSearch, 14. EMBEDDED SYSTEM IEEE PROJECTS - Automated Health Alerts, 15. Hot Spot Indemnity Visual Assistance by Raspberry Pi - ijsetr, 16. E health sensor platform for arduino and raspberry pi biometric - Imazi, 17. IOT BASED SMART HEALTHCARE KIT, 18. online healthcare system project documentation, 19. e healthcare ppt, 20. e health project in india, 21. online healthcare system project in java, 22. health care management system project in php, 23. healthcare project documentation, 24. online doctor consultation project, 25. e health project kerala, 26. GSM Patient Health Monitoring Project, 27. Patient health Monitoring through SMS using GSM modem, 28. Patient Monitoring System Using GSM Technology , 29. Microcontroller based Project on Patient Monitoring System - ElProCus, 30. Arduino And GSM Based Patient Health Monitoring System, 31. Health Monitoring with GSM | SMS Alerts for Health, 32. Android based Patient health monitoring system, 33. Final Year Projects | Health Care Management System, 34. Patients Health Care System Projects, 35. smart health prediction system, 36. smart health prediction using data mining pdf, 37. smart health prediction using data mining ieee, 38. smart health prediction using data mining ppt, 39. smart health prediction system ppt, 40. smart health prediction using data mining abstract, 41. smart health prediction using data mining ieee paper, 42. disease prediction using data mining seminar report, 43. IOT Patient Health Monitoring Project, 44. IOT Projects : Patient Health Monitoring System Using Raspberry Pi, 45. Health Monitoring and Management Using Internet-of-Things (IoT), 46. Internet of Things: Remote Patient Monitoring Using Web Services and, 47. PATIENT HEALTH MONITORING SYSTEM (PHMS) USING IoT, 48. Patient Health Monitoring System Using Raspberry Pi - IOT, 49. Health Monitoring using Internet of Things - IJSART, 50. IoT Based Remote Patient Health Monitoring System | Gandhian, 51. Patient Health Monitoring System using IOT and Android, 52. Design of Iot Based Smart Health Monitoring and Alert System, 53. iot based health monitoring system project ppt, 54. iot based health monitoring system ppt, 55. secured smart healthcare monitoring system based on iot, 56. iot based patient health monitoring system project, 57. patient health monitoring system project report, 58. internet of things: remote patient monitoring using web services and cloud computing, 59. iot based health monitoring system project using arduino, 60. iot based health monitoring system project report, 61. Virtual Care Taker-Online Patient Monitoring System, 62. IoT based patient health monitoring system, 63. IOT Patient Health Monitoring Project, 64. WARABLE HEALTH MONITORING SYSTEM USING IOT, 65. IoT based patient health monitoring system, 66. IOT 30 IOT Based Vehicle Health Monitoring System, 67. Healthcare Monitoring System Using Wireless Sensor Network, 68. Real Time Patient Health Monitoring and Alarming Using Wireless, 69. IoT and Cloud Server Based Wearable Health Monitoring System, 70. IOT (Internet of Things) based remote monitoring of patient body, 71. GSM Based Patient Health Monitoring Project, 72. WiFi Based Personal Health Monitoring System Using Android, 73. How to setup your own secure IoT cloud server, 74. Internet of Things (IoT) based Healthcare System - IIT Kanpur, 75. Patient Health Check Using Wireless Health Monitor, 76. IOT Based Health Monitoring project by Lokshith, 77. Wearable device to monitor patients health parameters, 78. Arduino And GSM Based Patient Health Monitoring System,
Views: 293 svsembedded