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Search results “Audio and video data mining ppt slides”
Audio Mining Enabler - Presentation
 
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A short presentation of the Audio Mining FIWARE Enabler developed by Fraunhofer IAIS, under the FIcontent project.
Views: 257 FIcontent
Data Structures and Algorithms Complete Tutorial Computer Education for All
 
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Computer Education for all provides complete lectures series on Data Structure and Applications which covers Introduction to Data Structure and its Types including all Steps involves in Data Structures:- Data Structure and algorithm Linear Data Structures and Non-Linear Data Structure on Stack Data Structure on Arrays Data Structure on Queue Data Structure on Linked List Data Structure on Tree Data Structure on Graphs Abstract Data Types Introduction to Algorithms Classifications of Algorithms Algorithm Analysis Algorithm Growth Function Array Operations Two dimensional Arrays Three Dimensional Arrays Multidimensional arrays Matrix operations Operations on linked lists Applications of linked lists Doubly linked lists Introductions to stacks Operations on stack Array based implementation of stack Queue Data Structures Operations on Queues Linked list based implementation of queues Application of Trees Binary Trees Types of Binary Trees Implementation of Binary Trees Binary Tree Traversal Preorder Post order In order Binary Search Tree Introduction to Sorting Analysis of Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Shell Sort Heap Sort Merge Sort Quick Sort Applications of Graphs Matrix representation of Graphs Implementations of Graphs Breadth First Search Topological Sorting Subscribe for More https://www.youtube.com/channel/UCiV37YIYars6msmIQXopIeQ Find us on Facebook: https://web.facebook.com/Computer-Education-for-All-1484033978567298 Java Programming Complete Tutorial for Beginners to Advance | Complete Java Training for all https://youtu.be/gg2PG3TwLx4
Data Analytics for Beginners | Introduction to Data Analytics | Data Analytics Tutorial
 
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Data Analytics for Beginners -Introduction to Data Analytics https://acadgild.com/big-data/data-analytics-training-certification?utm_campaign=enrol-data-analytics-beginners-THODdNXOjRw&utm_medium=VM&utm_source=youtube Hello and Welcome to data analytics tutorial conducted by ACADGILD. It’s an interactive online tutorial. Here are the topics covered in this training video: • Data Analysis and Interpretation • Why do I need an Analysis Plan? • Key components of a Data Analysis Plan • Analyzing and Interpreting Quantitative Data • Analyzing Survey Data • What is Business Analytics? • Application and Industry facts • Importance of Business analytics • Types of Analytics & examples • Data for Business Analytics • Understanding Data Types • Categorical Variables • Data Coding • Coding Systems • Coding, coding tip • Data Cleaning • Univariate Data Analysis • Statistics Describing a continuous variable distribution • Standard deviation • Distribution and percentiles • Analysis of categorical data • Observed Vs Expected Distribution • Identifying and solving business use cases • Recognizing, defining, structuring and analyzing the problem • Interpreting results and making the decision • Case Study Get started with Data Analytics with this tutorial. Happy Learning For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 251265 ACADGILD
Data Warehousing and Data Mining
 
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This course aims to introduce advanced database concepts such as data warehousing, data mining techniques, clustering, classifications and its real time applications. SlideTalk video created by SlideTalk at http://slidetalk.net, the online solution to convert powerpoint to video with automatic voice over.
Views: 4669 SlideTalk
How to explain Data Science Using Presentation Diagrams
 
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Download: https://www.infodiagram.com/diagrams/data_science_analytics_icons_ppt_flat.html?cp=camp5 What's Data Science? How it related to Big Data? And Data Mining? Example of simple visual explanation of areas that compose Data Science - A. data sources including Big Data, B. algorithm for processing data e.g. as statistics and machine learning algorithms C. business use. Illustration of data analysis process. See inspiration how you can present these popular data related concepts visually. Using simple charts and symbols. Adapt the presentation to your context. And let me know in comments how you did it :). I'd love to hear your opinion. All this is Do It Yourself graphics using Powerpoint. Read visualization tips on IT technology slide design on my https://blog.infodiagram.com Comments are welcome!
Web Mining - Tutorial
 
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Web Mining Web Mining is the use of Data mining techniques to automatically discover and extract information from World Wide Web. There are 3 areas of web Mining Web content Mining. Web usage Mining Web structure Mining. Web content Mining Web content Mining is the process of extracting useful information from content of web document.it may consists of text images,audio,video or structured record such as list & tables. screen scaper,Mozenda,Automation Anywhere,Web content Extractor, Web info extractor are the tools used to extract essential information that one needs. Web Usage Mining Web usage Mining is the process of identifying browsing patterns by analysing the users Navigational behaviour. Techniques for discovery & pattern analysis are two types. They are Pattern Analysis Tool. Pattern Discovery Tool. Data pre processing,Path Analysis,Grouping,filtering,Statistical Analysis, Association Rules,Clustering,Sequential Pattterns,classification are the Analysis done to analyse the patterns. Web structure Mining Web structure Mining is a tool, used to extract patterns from hyperlinks in the web. Web structure Mining is also called link Mining. HITS & PAGE RANK Algorithm are the Popular Web structure Mining Algorithm. By applying Web content mining,web structure Mining & Web usage Mining knowledge is extracted from web data.
Multimedia Presentation
 
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Here I present a presentation about Multimedia..... without audio......
Views: 45 Gamer Boy
What does Audio feature extraction and classification mean?
 
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One of the main reason that i am creating these videos are due to the problems i faced at the time of making presentation, so take the required info from this and make your presentation an informational one. Till now i got so many open source stuff so felt of offering the world so here are the efforts. Thank you I created this video with the YouTube Slideshow Creator (http://www.youtube.com/upload)
Views: 7103 Keep Going
Audio Analytic - A Promo Video
 
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http://www.audioanalytic.com - Audio Analytic is a company that produces software that automatically recognises sounds by means of computer analysis; audio analytics. The CoreLogger sound recognition software can detect a wide variety of sounds depending on the type of Sound Packs installed with high levels of ambient noise while still matching. Audio Analytic can also build new Sound Packs to order which can be used to compare and match against new audio streams or files. The award winning technology was developed as a result of three years of cutting edge research in sound recognition. Audio Analytic is based in Cambridge, UK. This video shows how their technology is used in modern security systems to detect aggression and glass break intrusion detection.
Views: 9044 audioanalytic
Final Year Projects 2015 | Predicting the Analysis of Heart Disease Symptoms
 
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Including Packages ===================== * 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: 5697 Clickmyproject
ANIME COLLEGE GIRLS NOT ALLOWED | SCREENCAPPED
 
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You got your anime girl license, mate? ▼ Patreon https://www.patreon.com/appabend ▼ SubscribeStar https://www.subscribestar.com/appabend ▼ PayPal https://www.paypal.me/appabend ▼ Ko-Fi https://ko-fi.com/appabend ▼ Twitter https://twitter.com/appabend ▼ Superchats https://streamlabs.com/appabend ▼ E-Mail [email protected] ==★★== ♫ INTRO ♫ Silent Partner - Which Way is Up [YT Audio Library] ♫ OUTRO ♫ HOME - We're Finally Landing https://youtu.be/eGigHoRQATs ★ CREDITS & RESOURCES ★ ~ AVATARS: ChrisDarkerArt https://www.fiverr.com/chrisdarkerart ~ SUIT: Shiromaki http://shiromaki.deviantart.com/ ~ VIDEO EDITOR: Vegas Pro 15 https://store.steampowered.com/app/883140/VEGAS_Pro_16_Edit_Steam_Edition/ ~ AUDIO EDITOR: Audacity http://www.audacityteam.org/ ~ SLIDES Microsoft PowerPoint 2016 ~ MICROPHONE Samson Q2U http://www.samsontech.com/samson/products/microphones/usb-microphones/q2u/ ~ MUSIC X-Files Theme ★ SAUCES ★ Steam Censorship https://youtu.be/BJmClzUszKM Steam Banning Game for Risk https://youtu.be/VQ3KnCZcn-Y Epic Games Store Debacles https://youtu.be/1drydx6PqAo https://youtu.be/k0k6Wn4X2-s Last on PUBG https://youtu.be/tZ0VJxElT_Y My Girlfriend Banned https://tinyurl.com/y366fbgo List of Banned Steam Anime Games https://tinyurl.com/y2o7u738 Dirty Education Not Banned https://tinyurl.com/yyhjed6r Sweet Pool NOT Banned https://tinyurl.com/y3orxp2w Naked Butlers NOT Banned https://tinyurl.com/y3tgd7uf Phoenix Point FIG Page https://tinyurl.com/yycecbn8 Phoenix Point NOT Going to Steam https://tinyurl.com/y37vfegr Epic Games Store Datamining https://tinyurl.com/y52yl8gs https://tinyurl.com/y3h8t37e MetaCouncil Forum Post https://tinyurl.com/y5o6klmf Arrested for PUBG http://archive.is/QuX48
Views: 15917 appabend
An Introduction to Linear Regression Analysis
 
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Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 737851 statisticsfun
CT Scan Kya Hota Hai ? | Computed Tomography Explained in Hindi
 
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Namaskar Dosto !! Is video me main aapko CT Scan ke bare me bataunga ki ye kya hota hai aur kaise kaam karta hai, aksar hospitals me ye kiya jata hai. aasha karta hu aapko ye video pasand ayegi. is video ko like kare aur apne dosto ke sath share kare aur agar aap is channel par naye aye hai to is channel ko subscribe kare kyu main aisi videos daily laata rehta hu. What is X - RAY: https://youtu.be/oinvXK9YCic What are Radiations: https://youtu.be/e7nrJ06766Q My Hacking Course: https://www.instamojo.com/technicalsagar/quick-hack-beginners-ethical-hacking-course-/ Buy Hacking Courses With Paytm: http://technicalsagar.in/paytm/ Subscribe to my channel for more videos like this and to support my efforts. Thanks and Love #TechnicalSagar LIKE | COMMENT | SHARE | SUBSCRIBE ---------------------------------------------------------------------------------- For all updates : LIKE My Facebook Page https://www.facebook.com/technicalsagarindia Follow Me on Twitter : http://www.twitter.com/iamasagar Follow Abhishek Sagar on Instagram: theabhisheksagar
Views: 192526 Technical Sagar
R programming for beginners – statistic with R (t-test and linear regression) and dplyr and ggplot
 
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R programming for beginners - This video is an introduction to R programming. I have another channel dedicated to R teaching: https://www.youtube.com/c/rprogramming101 In this video I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression). I also demonstrate how to use dplyr and ggplot to do data manipulation and data visualisation. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work. If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free. If you learn R programming you’ll have it for life. This video was sponsored by the University of Edinburgh. Find out more about their programmes at http://edin.ac/2pTfis2 This channel focusses on global health and public health - so please consider subscribing if you’re someone wanting to make the world a better place – I’d love to you join this community. I have videos on epidemiology, study design, ethics and many more.
Introduction to ANOVA
 
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statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!
Views: 398958 statslectures
What is DBMS ? & What is Database ? in Hindi (Simple Explain)
 
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Download PPT from Here: https://cuturl.in/8dVRca7k What is DBMS ? & What is Database ?: https://www.youtube.com/watch?v=PBLg4JWm-hg&t Advantages of DBMS: https://www.youtube.com/watch?v=iSBjEcZ1sdM&t Disadvantages of DBMS: https://www.youtube.com/watch?v=F0H5EmgFe94&t Database Users: https://www.youtube.com/watch?v=tp9rY46BSy0 Database Architecture: https://www.youtube.com/watch?v=zdABU1bVZDg&t ER Model: https://www.youtube.com/watch?v=VJUk-_CsqKw&t= Database Keys: https://www.youtube.com/watch?v=eA02pn64lrE&t Database (DBMS) Quiz Exam (MCQ): https://www.youtube.com/watch?v=wLeyxP6Y1Hs&t This is my Blog:- https://mystudymafia.blogspot.in/2018/02/what-is-dbms-what-is-database-dbms.html Keywords:- ------------------------------------------------------------------------------ What is DBMS in hindi & What is Database in hindi Define DBMS Define Database introduction to dbms in hindi definition of dbms definition of database Explain DBMS Explain Database in hindi What is Database Management System Define Database Management System Introduction to DBMS Introduction to Databases Database Lecture database tutorial for beginners DBMS Lecture hindi Database Management System DBMS and database DBMS Basic Advantages of DBMS in Hindi Advantages of Database Management System in Hindi advantages of database advantage of database Characteristics of DBMS in hindi Advantages of Database in hindi ------------------------------------------------------------------------------------------------
Views: 173563 STUDY Mafia
Final Year Projects 2015 | Mining Semantically Consistent Patterns for Cross-View Data
 
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Including Packages ======================= * 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: 267 Clickmyproject
The Importance of Being Stationary
 
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A PowerPoint presentation of about 60 slides with audio recorded at the original presentation. The presentation discusses the lack of stationarity of financial data and of trading systems, why that matters, and how to develop trading systems that are robust in spite of it. The books mentioned are available on Amazon.
Views: 8504 Howard B
Introduction to Database Management Systems 1: Fundamental Concepts
 
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This is the first chapter in the web lecture series of Prof. dr. Bart Baesens: Introduction to Database Management Systems. Prof. dr. Bart Baesens holds a PhD in Applied Economic Sciences from KU Leuven University (Belgium). He is currently an associate professor at KU Leuven, and a guest lecturer at the University of Southampton (United Kingdom). He has done extensive research on data mining and its applications. For more information, visit http://www.dataminingapps.com In this lecture, the fundamental concepts behind databases, database technology, database management systems and data models are explained. Discussed topics entail: applications, definitions, file based vs. databased data management approaches, the elements of database systems and the advantages of database design.
Views: 306218 Bart Baesens
SPSS for Beginners 1: Introduction
 
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Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.
Views: 1495345 Research By Design
Sampling & its 8 Types: Research Methodology
 
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Dr. Manishika Jain in this lecture explains the meaning of Sampling & Types of Sampling Research Methodology Population & Sample Systematic Sampling Cluster Sampling Non Probability Sampling Convenience Sampling Purposeful Sampling Extreme, Typical, Critical, or Deviant Case: Rare Intensity: Depicts interest strongly Maximum Variation: range of nationality, profession Homogeneous: similar sampling groups Stratified Purposeful: Across subcategories Mixed: Multistage which combines different sampling Sampling Politically Important Cases Purposeful Sampling Purposeful Random: If sample is larger than what can be handled & help to reduce sample size Opportunistic Sampling: Take advantage of new opportunity Confirming (support) and Disconfirming (against) Cases Theory Based or Operational Construct: interaction b/w human & environment Criterion: All above 6 feet tall Purposive: subset of large population – high level business Snowball Sample (Chain-Referral): picks sample analogous to accumulating snow Advantages of Sampling Increases validity of research Ability to generalize results to larger population Cuts the cost of data collection Allows speedy work with less effort Better organization Greater brevity Allows comprehensive and accurate data collection Reduces non sampling error. Sampling error is however added. Population & Sample @2:25 Sampling @6:30 Systematic Sampling @9:25 Cluster Sampling @ 11:22 Non Probability Sampling @13:10 Convenience Sampling @15:02 Purposeful Sampling @16:16 Advantages of Sampling @22:34 #Politically #Purposeful #Methodology #Systematic #Convenience #Probability #Cluster #Population #Research #Manishika #Examrace For IAS Psychology postal Course refer - http://www.examrace.com/IAS/IAS-FlexiPrep-Program/Postal-Courses/Examrace-IAS-Psychology-Series.htm For NET Paper 1 postal course visit - https://www.examrace.com/CBSE-UGC-NET/CBSE-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-CBSE-UGC-NET-Paper-I-Series.htm types of sampling types of sampling pdf probability sampling types of sampling in hindi random sampling cluster sampling non probability sampling systematic sampling
Views: 349297 Examrace
CRM systems in Hindi | What is Customers Relationship Management System in Urdu
 
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Learn what is CRM in Hindi,Urdu. Customer relationship Management or Client Relationship Management systems are used by organizations for maintaining relationships with the existing customers and prospected clients. Ifactner delivers this tutorial on CRM System in Hindi and Urdu languages to explain the concept, types and usage of Customer Relationship Management systems to Pakistani and Indians.
Views: 54903 ifactner technical
What Is A Multimedia Database?
 
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The extension of multimedia database systems. Googleusercontent search. Traditional databases contained 11 mar 2016 a multimedia database is that hosts one or more primary media file types such as. Multimedia is a combination of text, graphics, animations, audio and video converted from different formats into digital media. Characteristics of mdbmsdata types. A multimedia database (mmdb) is a collection of related data. Operations on data abstract. Mp3 17 sep 2008 organizationmm database system architecturemm service modelmultimedia data storage 19 dec 2012wei tsang ooimmdbms querying interface, indexing anda that is dedicated to the storage, management, and access of one or more media types, such as text, image, video, sound, diagram, etc from publisher multimedia management systems presents issues techniques used in building 10. Text audio graphic video animationmultimedia data typically means digital images, audio, video, animation and graphics together with text. A multimedia database is a that include one or more primary media file types such as. Multimedia database management system10. 10 multimedia database systems contents i4 lehrstuhl fuer multimedia database content and structure citeseerx. Multimedia database wikipedia multimedia wikipedia en. Multimedia databases are that contain and allow key data management operations with multimedia. The spatial, temporal, storage, retrieval, integration, and presentation requirements of multimedia data differ significantly abruce berra, 'multimedia database systems,' in lecture notes computer science, (advanced systems, edsbhargava n a management system (m dbms) should provide for the ef cient storage manipulation represented as text, images, voice, 28 feb 2011 purpose this study is to review current applications teaching learning, further discuss some issues a(mmdbms) must support types addition providing facilities traditional dbms functions controlled collection items such graphic objects, video audioMultimedia wikipediamultimedia slidesharemultimedia databasemultimedia tech faqintroduction youtubeigi global. Wikipedia wiki multimedia_database url? Q webcache. Multimedia database management systems acm digital library. The multimedia data include one or more primary media types such as text, images, graphic objects (including drawings, sketches and illustrations) animation sequences, audio video 20 dec 2015 database(mmdb)? Multimedia database is a collection of related. Multimedia database wikipediamultimedia slidesharemultimedia databasemultimedia the tech faqintroduction to multimedia youtubeigi global. Multimedia database management requirements citeseerxdistributed multimedia systems. The acquisition, generation a multimedia database management system (mm dbms) is framework that separate the and from application programs definition. Multimedia databases ieee xplore document. Multimedia database applications issues and concerns for multimedia systems where are we now? Itec.
Views: 450 Aile Aile
RESUME BUILDING FOR FRESHERS - PART 1 | Sample Resume Format | Resume Writing Tips
 
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FULL NAME Mobile: 0123456789 E-Mail: [email protected] (your name) OBJECTIVES (write your objectives in 3 sentences only) Very precise, short and should convey the message to the person reading it. For example : “To seek a position in a well established Organisation that offers room for professional growth, as this provides me ample opportunities to exhibit my skills and competencies in the chosen field”. ACADEMICS COURSES INSTITUTIONS BOARD YEAR OF PASSING % MBA (Marketing) XYZ School of Mgt. Bangalore University 2015 B.Com Name of College Name of university 2013 PUC (12th std) Name of College Name of university 2010 SSLC (10th std) Name of School Name of university 2008 PROJECTS (write a brief outline about your project, it should be structured & should highlight those points which would be beneficial for the current position’s interview) For example: Name of Co. : Western India Plywood’s ltd. Project Title : HR internship Project Outline : WIP is a public company which was started in the year 1945 and deals in the manufacturing and sales of both of plywood’s and hardwoods. The internship at Western India Plywood’s Ltd was for the duration of 3 month. During the tenure, I have hands on work in the areas mentioned below. • Functions of various departments in a company. • Assisted in the HR functionalities like Payroll database, Data Mining etc... • Was a part of the Exposure to launch an advertising campaign to attract more customers. PROFESSIONAL CERTIFICATIONS (Whatever certifications you have completed with relevant certificates &Specialisation). • Completed Advance Excel course from…..( Name of Institution / Centre ) • Completed Finance certification course …..( Name of Institution / Centre ) • SAP – (Domain specific: FICO, HCM, MM etc….) • Certified Six Sigma – Orange Belt, passed with distinction ACCOLADES ( Any awards and recognitions received ) • Presented Papers in the College / Inter College Journals • Represented College in Management Programs & Seminars • Nominated as the Best Student for….(any awards you can mention) COMPUTER PROFICIENCY (only if you have done some course or diploma) • Sound Knowledge in ERP, SAP Platforms • JAVA , C++ courses PERSONAL SKILLS (Write strengths based on your Major / minor specialisation, you can also relate your skills to the projects or events who might be part of & highlight them during an interview ) • Effective Client Relations • Quick Learner • Self Confidence & Positive Attitude • Ability to perform & contribute under pressure • Flexible & Adaptable to changes & challenges • Highly Self Motivated • Ability to work with Team EXTRA CURRICULAR ACTIVITES • Involved in raising Funds for NGOs • Participated in various Cultural Committee Development activities • Involved in CSR assignments for the college • Participated in Dance & Sports events conducted in Colleges • Participated in Management Fest & Inter College a Fests PERSONAL DOSSIER • Date of Birth : (Your Date of Birth) • Gender : Male/Female • Linguistic Proficiency : Read: - English, Hindi, (language u know to read only) Write: - English, Hindi (languages u know to write only) • LinkedIn Profile : ( Paste the Url link ) • Twitter Profile : ( Paste the Url link ) Declaration: I hereby declare that the information furnished above is true and to the best of my knowledge & belief. Place: Date: (FULL NAME) Disclaimer: The content written and spoken in this video are the soul property of Cassius Technologies Pvt Ltd. In case of any resemblance to any sites or any videos are mere coincidence.
What is Internet? In Hindi
 
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What is Internet? In Hindi. इन्टरनेट क्या है? हिन्दी में Click here for more tips and tricks information: http://www.aniskhan.in If you are looking for some more information about Internet so here is the beautiful video explaining concept of Internet. Most of the people are using internet frequently but not aware What is Internet or don't know Internet meaning. Internet Means International network of Computers. Here you will come to know What is internet of things in Hindi. Please watch full video to understand meaning of Internet. =================== For new episodes every week, subscribe here! https://www.youtube.com/c/aniskhanmedia Like us on Facebook : https://www.facebook.com/aniskhanmedia Follow us on Twitter: https://twitter.com/aniskhanmedia Find out more about Anis Khan: http://www.aniskhan.in =================== What is Internet? In Hindi
Views: 352391 Anis Khan
Google's Deep Mind Explained! - Self Learning A.I.
 
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Subscribe here: https://goo.gl/9FS8uF Become a Patreon!: https://www.patreon.com/ColdFusion_TV Visual animal AI: https://www.youtube.com/watch?v=DgPaCWJL7XI Hi, welcome to ColdFusion (formally known as ColdfusTion). Experience the cutting edge of the world around us in a fun relaxed atmosphere. Sources: Why AlphaGo is NOT an "Expert System": https://googleblog.blogspot.com.au/2016/01/alphago-machine-learning-game-go.html “Inside DeepMind” Nature video: https://www.youtube.com/watch?v=xN1d3qHMIEQ “AlphaGo and the future of Artificial Intelligence” BBC Newsnight: https://www.youtube.com/watch?v=53YLZBSS0cc http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html http://www.ft.com/cms/s/2/063c1176-d29a-11e5-969e-9d801cf5e15b.html http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html#tables https://www.technologyreview.com/s/533741/best-of-2014-googles-secretive-deepmind-startup-unveils-a-neural-turing-machine/ https://medium.com/the-physics-arxiv-blog/the-last-ai-breakthrough-deepmind-made-before-google-bought-it-for-400m-7952031ee5e1 https://www.deepmind.com/ www.forbes.com/sites/privacynotice/2014/02/03/inside-googles-mysterious-ethics-board/#5dc388ee4674 https://medium.com/the-physics-arxiv-blog/the-last-ai-breakthrough-deepmind-made-before-google-bought-it-for-400m-7952031ee5e1#.4yt5o1e59 http://www.theverge.com/2016/3/10/11192774/demis-hassabis-interview-alphago-google-deepmind-ai https://en.wikipedia.org/wiki/Demis_Hassabis https://en.wikipedia.org/wiki/Google_DeepMind //Soundtrack// Disclosure - You & Me (Ft. Eliza Doolittle) (Bicep Remix) Stumbleine - Glacier Sundra - Drifting in the Sea of Dreams (Chapter 2) Dakent - Noon (Mindthings Rework) Hnrk - fjarlæg Dr Meaker - Don't Think It's Love (Real Connoisseur Remix) Sweetheart of Kairi - Last Summer Song (ft. CoMa) Hiatus - Nimbus KOAN Sound & Asa - This Time Around (feat. Koo) Burn Water - Hide » Google + | http://www.google.com/+coldfustion » Facebook | https://www.facebook.com/ColdFusionTV » My music | t.guarva.com.au/BurnWater http://burnwater.bandcamp.com or » http://www.soundcloud.com/burnwater » https://www.patreon.com/ColdFusion_TV » Collection of music used in videos: https://www.youtube.com/watch?v=YOrJJKW31OA Producer: Dagogo Altraide Editing website: www.cfnstudios.com Coldfusion Android Launcher: https://play.google.com/store/apps/details?id=nqr.coldfustion.com&hl=en » Twitter | @ColdFusion_TV
Views: 3048140 ColdFusion
IEEE 2017:A Workflow Management System for Scalable Data Mining on Clouds
 
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We are ready to provide guidance to successfully complete your projects and also download the abstract, base paper from our website Note: Voice Video Listen with audio Visit : www.javafirst.in Contact: 73383 45250
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: 455997 Brandon Weinberg
Nu-Oil - AGM Presentation 2018
 
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This video is an audio powerpoint of the presentation given at our Annual General Meeting on the 24 January 2018. If you have any further questions, please contact us at [email protected]
Views: 818 Nu-Oil and Gas plc
HPLC chromatography
 
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HPLC chromatography lecture - This lecture explains about the HPLC chromatography technique in a nutshell by Suman Bhattacharjee. HPLC is performed to separate organic and biological compounds using solid stationary phase. High Performance Liquid Chromatography (HPLC) is a form of column chromatography that pumps a sample mixture or analyte in a solvent which is known as the mobile phase at high pressure through a column with chromatographic packing material known as stationary phase. The sample is carried by a moving carrier gas stream of helium or nitrogen. HPLC has the ability to separate, and identify compounds that are present in any sample that can be dissolved in a liquid in trace concentrations as low as parts per trillion. Because of this versatility, HPLC is used in a variety of industrial and scientific applications, such as pharmaceutical, environmental, forensics, and chemicals. Sample retention time will vary depending on the interaction between the stationary phase, the molecules being analyzed, and the solvent, or solvents used. As the sample passes through the column it interacts between the two phases at different rate, primarily due to different polarities in the analytes. Analytes that have the least amount of interaction with the stationary phase or the most amount of interaction with the mobile phase will exit the column faster. This lecture explains the following things about Hplc chromatography - 1. Hplc chromatography principle 2. Hplc chromatography instrumentation 3. Hplc chromatography types High-Performance Liquid Chromatography - Other HPLC Types Ultra High Performance Liquid Chromatography (uHPLC): Where standard HPLC typically uses column particles with sizes from 3 to 5µm and pressures of around 400 bar, uHPLC use specially designed columns with particles down to 1.7µm in size, at pressures in excess of 1000 bar. The main advantage of an uHPLC is speed. These systems are faster, more sensitive, and rely on smaller volumes of organic solvents than standard HPLC, resulting in the ability to run more samples in less time. Article source: http://hiq.linde-gas.com/en/analytical_methods/liquid_chromatography/high_performance_liquid_chromatography.html For more information, log on to- http://www.shomusbiology.com/ Get Shomu's Biology DVD set here- http://www.shomusbiology.com/dvd-store/ Download the study materials here- http://shomusbiology.com/bio-materials.html Remember Shomu’s Biology is created to spread the knowledge of life science and biology by sharing all this free biology lectures video and animation presented by Suman Bhattacharjee in YouTube. All these tutorials are brought to you for free. Please subscribe to our channel so that we can grow together. You can check for any of the following services from Shomu’s Biology- Buy Shomu’s Biology lecture DVD set- www.shomusbiology.com/dvd-store Shomu’s Biology assignment services – www.shomusbiology.com/assignment -help Join Online coaching for CSIR NET exam – www.shomusbiology.com/net-coaching We are social. Find us on different sites here- Our Website – www.shomusbiology.com Facebook page- https://www.facebook.com/ShomusBiology/ Twitter - https://twitter.com/shomusbiology SlideShare- www.slideshare.net/shomusbiology Google plus- https://plus.google.com/113648584982732129198 Thank you for watching HPLC lecture
Views: 529508 Shomu's Biology
Blinking Hell - Data extraction through keyboard lock states (BSides London 2013 Presentation)
 
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A video of our BSides London 2013 presentation on the rookie track for Blinking Hell. It was the first time presenting for either of us, but we both agree it was a brilliant time. Muchos thanks goes out to everyone responsible for organising the Rookie Track this year, was a brilliant idea and well executed. Basic Premise: Plug in teensy device, use a macro to export data to it using the caps/scroll/num lock keys, collect teensy device at a later date. Circumvents device filters based on vendor/product ID. Can be left in location for many months before collecting data and can be put back into a "waiting mode" to collect more data at a later date before being collected from the premises (thats the next bit we're working on at least ;)) Read more about this at - My Blog: http://x.co/1CBu9 Matts Blog: http://x.co/1CBxn Links to code can be found on my blog, along with follow up links to a copy of the slides and videos. However here's a quick link to the assembla repository that includes our code, and presentation materials. http://x.co/1CBzC Editing was done with kdenlive.
Views: 101 Script Monkey
Mining Administrative Data: Identifying and Understanding At-Risk Populations
 
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A version of this video with audio description can be accessed at https://youtu.be/BjT10KsWCOY. In this webinar hosted by James Bell Associates on May 18, 2017, Dr. Dana Weiner discusses strategies for mining administrative data for the purpose of assessing the characteristics and needs of at-risk child welfare populations. Using examples from a federal Permanency Innovations Initiative (PII) grantee in Illinois, Dr. Weiner identifies the key requirements of productive data mining, steps in the data mining process, and useful statistical techniques for analyzing and making sense of administrative data. We accept comments in the spirit of our comment policy: https://www.hhs.gov/web/socialmedia/policies/comment-policy.html
Views: 59 usgovACF
What is Bitcoin Mining?
 
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For more information: https://www.bitcoinmining.com and https://www.weusecoins.com What is Bitcoin Mining? Have you ever wondered how Bitcoin is generated? This short video is an animated introduction to Bitcoin Mining. Credits: Voice - Chris Rice (www.ricevoice.com) Motion Graphics - Fabian Rühle (www.fabianruehle.de) Music/Sound Design - Christian Barth (www.akkord-arbeiter.de) Andrew Mottl (www.andrewmottl.com)
Views: 6762652 BitcoinMiningCom
Report 13: 2015-16 Cloud computing audio presentation
 
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This report examines whether Queensland Government departments are using cloud technology to deliver business value while managing the risks.
(Hindi)What is Business Process Outsourcing(BPO)?
 
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This video explains it all about BPO(Business Process Outsourcing) in Hindi. For more awesome Business videos, click here to subscribe- https://goo.gl/feR2v3 Smartphone(Camera) I use to Record_ http://fkrt.it/us0y7!NNNN Stay connected with Business Block at; Facebook- https://www.facebook.com/BusinessBlockPage/ Instagram- https://www.instagram.com/business_block/ Twitter- https://twitter.com/Business_Block Google Plus- https://plus.google.com/109642995027385576089 If you like the videos, Do share them!
Views: 149578 Business Block
IEEE 2016: Sentiment Analysis of Top Colleges in India Using Twitter Data
 
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We are ready to provide guidance to successfully complete your projects and also download the abstract, base paper from our website Note: Voice Video Listen with audio Visit : www.javafirst.in Contact: 73383 45250
The CMSR Data Suite
 
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A brief discussion on the CMSR Data Suite Music: Dreams by Joakim Karud https://soundcloud.com/joakimkarud Creative Commons — Attribution-ShareAlike 3.0 Unported— CC BY-SA 3.0 http://creativecommons.org/licenses/b... Music provided by Audio Library https://youtu.be/VF9_dCo6JT4
Views: 67 thepersonwho
What is Encryption and Decryption ? | Concept Explained (in Hindi)
 
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In this video we will discuss about encryption and decryption. How these things works and why we need these. Watch the full video to know more about this topic. Like the video and please share with your friends. Subscribe to my channel for more video like this and to support my effort. Catch me on Social Networking Websites Like my Facebook Page: https://www.facebook.com/technicalsagarindia Twitter: https://twitter.com/iamasagar
Views: 118685 Technical Sagar
Multimedia Answering: Enriching Text QA with Media Information
 
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Existing community question-answering forums usually provide only textual answers. For many questions, however, pure text cannot provide intuitive information as this is better conveyed through image or video. In this invention a scheme to enrich text answers with image and video is introduced. Given a question and the community-contributed answer, this method utilizes several techniques to enrich textual answers like question/answer classification, query generation, image and video search reranking, etc. Different from some efforts that attempt to directly answer questions with image and video data, this method leverages community-contributed textual answers and thus is able to deal more effectively with more complex questions.
Views: 1192 jz00hj
ISO 9001:2015 PDF CHECKLIST | PDF Guide to ISO 9001 Quality Management Systems
 
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ISO 9001:2015 PDF checklist DOWNLOAD below! ISO 9001 online training course presented by CEO Kobi Simmat. An advanced, step-by-step breakdown of our ISO 9001:2015 PDF checklist. Go and dive into our amazing ISO 9001:2015 Gap Analysis Checklist Course that we have available as the perfect introduction and implementation tool to accompany your management system https://bit.ly/2SGswGm Follow and subscribe to: Best Practice Website : https://goo.gl/uJTioQ Facebook : https://goo.gl/VOJfKZ LinkedIn : https://goo.gl/dZmlTr Youtube : https://goo.gl/8SVD9E Instagram : @bestpracticetv Snapchat : @bestpracticetv Dreams by Joakim Karud https://soundcloud.com/joakimkarud Creative Commons — Attribution-ShareAlike 3.0 Unported— CC BY-SA 3.0 http://creativecommons.org/licenses/b... Music provided by Audio Library https://youtu.be/VF9_dCo6JT4
Views: 82085 @BestPracticeTV
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: 753177 Dr Nic's Maths and Stats
How DTW (Dynamic Time Warping) algorithm works
 
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In this video we describe the DTW algorithm, which is used to measure the distance between two time series. It was originally proposed in 1978 by Sakoe and Chiba for speech recognition, and it has been used up to today for time series analysis. DTW is one of the most used measure of the similarity between two time series, and computes the optimal global alignment between two time series, exploiting temporal distortions between them. Source code of graphs available at https://github.com/tkorting/youtube/blob/master/how-dtw-works.m The presentation was created using as references the following scientific papers: 1. Sakoe, H., Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoustic Speech and Signal Processing, v26, pp. 43-49. 2. Souza, C.F.S., Pantoja, C.E.P, Souza, F.C.M. Verificação de assinaturas offline utilizando Dynamic Time Warping. Proceedings of IX Brazilian Congress on Neural Networks, v1, pp. 25-28. 2009. 3. Mueen, A., Keogh. E. Extracting Optimal Performance from Dynamic Time Warping. available at: http://www.cs.unm.edu/~mueen/DTW.pdf
Views: 36209 Thales Sehn Körting
Scales of Measurement - Nominal, Ordinal, Interval, Ratio (Part 1) - Introductory Statistics
 
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This video reviews the scales of measurement covered in introductory statistics: nominal, ordinal, interval, and ratio (Part 1 of 2). Scales of Measurement Nominal, Ordinal, Interval, Ratio YouTube Channel: https://www.youtube.com/user/statisticsinstructor Subscribe today! Lifetime access to SPSS videos: http://tinyurl.com/m2532td Video Transcript: In this video we'll take a look at what are known as the scales of measurement. OK first of all measurement can be defined as the process of applying numbers to objects according to a set of rules. So when we measure something we apply numbers or we give numbers to something and this something is just generically an object or objects so we're assigning numbers to some thing or things and when we do that we follow some sort of rules. Now in terms of introductory statistics textbooks there are four scales of measurement nominal, ordinal, interval, and ratio. We'll take a look at each of these in turn and take a look at some examples as well, as the examples really help to differentiate between these four scales. First we'll take a look at nominal. Now in a nominal scale of measurement we assign numbers to objects where the different numbers indicate different objects. The numbers have no real meaning other than differentiating between objects. So as an example a very common variable in statistical analyses is gender where in this example all males get a 1 and all females get a 2. Now the reason why this is nominal is because we could have just as easily assigned females a 1 and males a 2 or we could have assigned females 500 and males 650. It doesn't matter what number we come up with as long as all males get the same number, 1 in this example, and all females get the same number, 2. It doesn't mean that because females have a higher number that they're better than males or males are worse than females or vice versa or anything like that. All it does is it differentiates between our two groups. And that's a classic nominal example. Another one is baseball uniform numbers. Now the number that a player has on their uniform in baseball it provides no insight into the player's position or anything like that it just simply differentiates between players. So if someone has the number 23 on their back and someone has the number 25 it doesn't mean that the person who has 25 is better, has a higher average, hits more home runs, or anything like that it just means they're not the same playeras number 23. So in this example its nominal once again because the number just simply differentiates between objects. Now just as a side note in all sports it's not the same like in football for example different sequences of numbers typically go towards different positions. Like linebackers will have numbers that are different than quarterbacks and so forth but that's not the case in baseball. So in baseball whatever the number is it provides typically no insight into what position he plays. OK next we have ordinal and for ordinal we assign numbers to objects just like nominal but here the numbers also have meaningful order. So for example the place someone finishes in a race first, second, third, and so on. If we know the place that they finished we know how they did relative to others. So for example the first place person did better than second, second did better than third, and so on of course right that's obvious but that number that they're assigned one, two, or three indicates how they finished in a race so it indicates order and same thing with the place finished in an election first, second, third, fourth we know exactly how they did in relation to the others the person who finished in third place did better than someone who finished in fifth let's say if there are that many people, first did better than third and so on. So the number for ordinal once again indicates placement or order so we can rank people with ordinal data. OK next we have interval. In interval numbers have order just like ordinal so you can see here how these scales of measurement build on one another but in addition to ordinal, interval also has equal intervals between adjacent categories and I'll show you what I mean here with an example. So if we take temperature in degrees Fahrenheit the difference between 78 degrees and 79 degrees or that one degree difference is the same as the difference between 45 degrees and 46 degrees. One degree difference once again. So anywhere along that scale up and down the Fahrenheit scale that one degree difference means the same thing all up and down that scale. OK so if we take eight degrees versus nine degrees the difference there is one degree once again. That's a classic interval scale right there with those differences are meaningful and we'll contrast this with ordinal in just a few moments but finally before we do let's take a look at ratio.
Views: 355127 Quantitative Specialists
Text Mining for Beginners
 
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This is a brief introduction to text mining for beginners. Find out how text mining works and the difference between text mining and key word search, from the leader in natural language based text mining solutions. Learn more about NLP text mining in 90 seconds: https://www.youtube.com/watch?v=GdZWqYGrXww Learn more about NLP text mining for clinical risk monitoring https://www.youtube.com/watch?v=SCDaE4VRzIM
Views: 77254 Linguamatics
Hazard Identification and Risk Assessment (HIRA) Part-1/3 (Hindi) HD | Safety Training | Team OHSE
 
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Hazard: Anything (e.g. condition, situation, practice, behavior) that has the potential to cause harm, including injury, disease, death, environmental, property and equipment damage. A hazard can be a thing or a situation. Hazard Identification: This is the process of examining each work area and work task for the purpose of identifying all the hazards which are “inherent in the job”. Work areas include but are not limited to machine workshops, laboratories, office areas, agricultural and horticultural environments, stores and transport, maintenance and grounds, reprographics, and lecture theatres and teaching spaces. Tasks can include (but may not be limited to) using screen-based equipment, audio and visual equipment, industrial equipment, hazardous substances and/or teaching/dealing with people, driving a vehicle, dealing with emergency situations, construction. This process is about finding what could cause harm in work task or area. Risk: The likelihood, or possibility, that harm (injury, illness, death, damage etc) may occur from exposure to a hazard. Risk Assessment: Is defined as the process of assessing the risks associated with each of the hazards identified so the nature of the risk can be understood. This includes the nature of the harm that may result from the hazard, the severity of that harm and the likelihood of this occurring. Please Be SAFE & ALERT. Trainer's Name - Mohd. Syeed Siddiqui https://www.linkedin.com/in/mohdsyeeds/ For any business related queries, please contact - [email protected] Like Us on Facebook www.fb.com/teamohse Follow us on Instagram @teamohse
Views: 58650 Team OHSE
Business Data Communications Interview (Sample) | Center for eLearning
 
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Develop for one of FSCJ's many Information Technology courses, this video gives students a rare view into what it takes to be an industry professional. The interviewee is Colo5 Data Center sales executive, Johnny Helms. FSCJ: The Center for eLearning Multimedia Team Motion Graphic - Eduardo Rodriguez Filming - Eduardo Rodriguez Video Edit - Eduardo Rodriguez Audio - Eduardo Rodriguez
Views: 192 FSCJ Jacksonville
ACM Multimedia 2012 Grand Challenge: Classification of Photos based on Good Feelings
 
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This is a presentation I gave at ACM MM 2012 in Nara Japan. It shows our prototype application to classify images based on the intentions of the photographers in 3 minutes. The audio stream has been pre-recorded :) The original paper, the demo application and the test datas set used for training the classifier is available here: http://www.itec.uni-klu.ac.at/~mlux/intentions-data-set.htm
Views: 605 Mathias Lux
Linking the Time and Frequency Domain
 
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Summary: Both the time and frequency domains provide unique insight into road load and vibration data. This presentation will explore how the best of both techniques - called joint time-frequency analysis - can provide further visualization and analysis capabilities. Presenter: Andrew Halfpenny, Chief Technologist, HBM-nCode Originally presented on May 15, 2014 at the 2014 HBM-nCode Products User Group Meeting in Livonia, Michigan (USA). For more information, visit https://www.ncode.com/products-yt
Views: 4557 nCode Software
How SVM (Support Vector Machine) algorithm works
 
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In this video I explain how SVM (Support Vector Machine) algorithm works to classify a linearly separable binary data set. The original presentation is available at http://prezi.com/jdtqiauncqww/?utm_campaign=share&utm_medium=copy&rc=ex0share
Views: 523024 Thales Sehn Körting