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Data Science for Business: Data Mining Process and CRISP DM
 
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This lesson provides an introduction to the data mining process with a focus on CRISP-DM. This video was created by Cognitir (formerly Import Classes). Cognitir is a global company that provides live training courses to business & finance professionals globally to help them acquire in-demand tech skills. For additional free resources and information about training courses, please visit: www.cognitir.com
Views: 16050 Cognitir
KDD ( knowledge data discovery )  in data mining in hindi
 
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#kdd #datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 86317 Last moment tuitions
data mining techniques
 
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This video describes data mining tasks or techniques in brief. Each technique requires a separate explanation as well. #datamining #techniques #weka Data mining tutorial in hindi Weka tutorial in hindi Data mining tutorial
Views: 9395 yaachana bhawsar
data mining methodology
 
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Views: 1375 Allan Esser
Introduction to data mining and architecture  in hindi
 
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#datamining #datawarehouse #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 257061 Last moment tuitions
A Review Paper on Dengue Disease Forcasting Using Data Mining Techniques
 
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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: 61 Clickmyproject
Data mining
 
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Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term is a misnomer, because the goal is the extraction of patterns and knowledge from large amount of data, not the extraction of data itself. It also is a buzzword, and is frequently also applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence, machine learning, and business intelligence. The popular book "Data mining: Practical machine learning tools and techniques with Java" (which covers mostly machine learning material) was originally to be named just "Practical machine learning", and the term "data mining" was only added for marketing reasons. Often the more general terms "(large scale) data analysis", or "analytics" -- or when referring to actual methods, artificial intelligence and machine learning -- are more appropriate. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 1712 Audiopedia
Crisp DM
 
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Views: 195 Mneria De Datos
CRISP-DM: how to bring analytics to production
 
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An agile way to bring analytics to production in a business-oriented and systematic way is CRISP-DM model.
Procesos estándares CRISP - DM
 
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#SesiónBs Compartimos la sesión “Procesos estándares CRISP-DM” correspondiente al primer capítulo del Programa Certified Big Data & Machine Learning Professional. ►Más Información: https://goo.gl/xGkiun
Views: 658 BSG Institute
What is Data Mining ? | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) Data mining is the process of digging out useful and interesting knowledge from large amounts of data. R is a free software environment, which provides a wide variety of statistical and graphical techniques meant for statistical computing and graphics. R provides comprehensive collections of packages for different tasks involved in data mining. Watch this video to get some more insight into what data mining is, along with the following topics: 1. What is Data Mining? 2. Why Data Mining? 3. CRISP-DM, KDD and SEMMA 4. Advanced techniques in Data Mining in R 5. Multiple data mining methods using RATTLE Related Posts: http://www.edureka.co/blog/k-means-clustering/ 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 Data Mining and R have extensively been covered in our course ‘Business Analytics with R’. 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: 37027 edureka!
Colin Shrearer: Crisp DM
 
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CRISP-DM - the standard model for analytics progress
Views: 1025 Houston Analytics Oy
SAS EMiner: Setup and Introduction
 
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This video describes a simple setup for running a workstation version of SAS Enterprise Miner. It explains the necessary directory structure, the steps taken in the creation of a new project, a method of importing a CSV data file and its inspection. The lesson also gives a very quick preview of a very simple analytic process, aiming at predicting the survival of the Titanic passengers, and involving data sampling, exploration, modelling and assessment - part of the SAS SEMMA methodology. The explanation will be quite informal and will avoid the more complex machine learning concepts. The data for this lesson can be obtained from the well-known Kaggle web site for Data Science resources: * https://www.kaggle.com/c/titanic/data Videos in data analytics and data visualization by Jacob Cybulski, SAS Visual Analytics Collaboratory at Deakin University.
Views: 2776 ironfrown
Proceso KDD y CRISP-DM
 
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Proceso de descubrimiento de conocimiento (KDD) y fases detalladas de CRISP-DM. Grabado el 7 de marzo de 2018 6:50 p.m. hora Colombia.
Views: 682 Carlos Cobos
ST MARIA TRAINING INSTITUTE
 
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St. Maria Training Institute is the best Institute in Tanzania that provides quality education to the Society. But also St. Maria enables all youth and Adult to acquire Skills and Knowledge in all courses that is provided in our college to both women and men. LOCATION St.Maria Training Institute is located in Mwanza region.Ilemela District,Kirumba Ward in Tanzania East Africa. MISSION Is to provide quality education in Certificate which offered by our college. In our college we offer the following Courses 1. Hospitality and Tourism 2. Domestic and Industrial Electrical Installation 3. Audio and Video Production 4. Computer Repair and Maintenance 5. Basic Computer Application 6. Computer Networking 7. Web Designing 8. Secretarial Courses 9. Mining Courses But also we are expecting to offer the following courses in future: a) Nursing b) Welding and Fabrication c) Automobile Electrical Installation OBJECTIVE • To provide high quality skills and knowledge to young people in order to reduce unemployment for the young people in the country. • To provide free service to all young people who are coming from poor family • Also the college is providing counseling and guidance in HVI and Environmental conservation as well as Entrepreneurship to the society. • But also we advise young people to stop smoking and alcoholic drinks. Building We have Modern building with enough rooms to all staff and class rooms found at Kigoto Moravian church. OFFER St Maria provides the service to the society as offer as follows: a) To provide free service to all young people who are coming from poor family; street children, Orphans etc. b) Also we provide service to widow that lives with HIV etc. The service which we provide to those who are mentioned above in order to employ themselves are: a) How to make bar soap b) Batic & kikoi c) Liquid soap d) Juice e) Snuks f) Honey g) Agricultural Services h) To produce different food like biscuit, sweets,cakes etc i) To make carpet j) To provide education on how to manage small business and on how to make min-plan in order to run well their business.
Views: 150 MARIA TRAINING
CRISP DM - Sharing Bike System
 
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The description of project
Views: 106 zhengyu1310
Metodología Crisp-DM
 
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Aprende en este vídeo tutorial qué es la metodología Crisp-DM para Data Scientist
Semma Therapeutics
 
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Felicia Pagliuca, Ph.D., Co-Founder and VP, Cell Biology Research and Development Cambridge, MA (Private) Semma Therapeutics was founded to develop transformative therapies for Type 1 diabetes patients. Work in the laboratory of Professor Douglas Melton led to the discovery of a method to generate billions of functional, insulin-producing beta cells in vitro. This breakthrough technology has been exclusively licensed to Semma Therapeutics for the development of a cell-based therapy for diabetes. Ongoing research at Semma Therapeutics is focused on combining these proprietary cells with its state-of-the-art device to provide a true replacement for the missing beta cells in a diabetic patient without the need for immunosuppression. Semma Therapeutics is working to bring new therapeutic options to the clinic and improve the lives of patients with diabetes. The company is headquartered in Cambridge, MA, and was founded in 2015 with financing led by MPM Capital, F-Prime Capital and strategic investors Novartis and Medtronic. www.semma-tx.com
Hybrid Data Mining Techniques for the Generation of Functional Genomic Relations
 
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Hybrid Data Mining Techniques for the Generation of Functional Genomic Relations at the First Meeting of the USTHB Computing Research Club by Boutorh Aicha
Views: 272 TechTalks DZ
DATA MINING EXPLAINED IN HINDI | "ITNA SARA DATA??"
 
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नमस्कार दोस्तों,आज की वीडियो में में आप सभी को DATA MINING के बारे में बताने जा रहा हूँ की आखिर DATA MINING क्या होती है और क्या ये हमारे किसी काम आती हैं या नहीं और आखिर हमारे ज़िन्दगी में इसकी कितनी जरुरत है। आशा करता हूँ आपको ये वीडियो पसंद आएगी अगर आपको वीडियो पसंद आये तो वीडियो को LIKE SHARE और चैनल को SUBSCRIBE जरूर से करे। धन्यवाद। जय हिन्द वन्दे मातरम subscribe our channel on youtube: https://www.youtube.com/channel/UCR_kAPwG59SxWRaUfzk3qoQ facebook: https://www.facebook.com/dropouttechnical/ twitter: https://twitter.com/dropoutechnical google+: https://plus.google.com/u/0/103031877017890269380 -~-~~-~~~-~~-~- Please watch: "MOTO X4 my opinion |"Best phone??"|"worth buy at 21000"🔥" https://www.youtube.com/watch?v=r54C6_667uU -~-~~-~~~-~~-~-
Views: 14649 Dropout Technical
Basic Star Schema design
 
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Among the most basic design skills in designing a data warehouse solution is the star schema design. What's a star schema? What are the characteristics of a good star design?
Views: 110943 Rob Kerr
SAS EM Interface
 
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Understanding SAS Enterprise Miner interface
Views: 211 Dothang Truong
Ontology Search Based on Similarity in OOSP
 
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The extension of Online Ontology Set Picker (OOSP) tool for selecting similar ontologies from ontology collections available via OOSP.
Views: 137 Ondrej Zamazal
L8/P3: Environment Clearance- ELMA, NEMA, SEMA, Public hearing, Linear infra.
 
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Language: Hindi, Topics Covered: 1. Environment Clearance: why delays, Proposed environment laws management act (ELMA 2014) 2. Proposed statutory bodies: National Environment Management Authority (NEMA), SEMA, UTEMA- their structure, functions and jurisdiction over category A and B projects. 3. Fast tracking of public hearing and linear projects- why activists are angry? 4. compensatory afforestation- need for reforms, environment reconstruction fund 5. Pollution control: municipal waste, vehicle pollution, noise pollution 6. Proposed new All India Environment services and reforms in higher education in environment sector. 7. Mock question for mains: The principal aim of Environment regulation should be to balance Ecological & Economic needs of India. Critically examine the lacunas in present legal-Administrative framework & suggest remedies. 8. Mock Essay for Mains: Nature is the source of all material things: the Maker, the means of making, and the things made. (Isha Upanishad) 9. Mock Essay for Mains: “Environmental conservation is about negotiating the transition from past to future in such a way as to secure the transfer of maximum significance.” (Holland and Rawles, 1930) Powerpoint available at http://Mrunal.org/download Exam-Utility: UPSC IAS IPS, CSAT, Prelims, Mains, CDS, CAPF, Bank, RBI, IBPS, SSC and other competitive exams, IIM, XLRI, MBA interviews and GDPI Faculty Name: Mrunal Patel Venue: Sardar Patel Institute of Public Administration (SPIPA), Satellite, Ahmedabad, Gujarat,India
Views: 104590 Mrunal Patel
mSOS: Mobile SMS-based disease outbreak alert system in Kenya
 
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mSOS is a SMS-based disease notification system where health care workers immediately relay information on suspected priority diseases to sub-county, county and national MOH officials by sending structured SMS messages to a toll-free number. The system can be used on both basic mobile phones and smartphones. mSOS is also equipped with a password-protected web portal where maps, epidemic graphs and tables of suspected incidences (based on SMS notifications sent via mSOS) and response actions (based on reports by the MOH, county and sub-county disease surveillance coordinators) are displayed on the web portal in real-time. All information is displayed and reviewed in real-time, and all data is stored at a server owned by the MOH. MOH officials use these tools to map incidences and plan outbreak containment measures. Priority diseases are mainly classified into three categories: epidemic prone diseases, diseases targeted for elimination or eradication, and diseases/conditions and events of public health significance. For example, if a physician sees a patient with symptoms consistent with Ebola, he/she can use mSOS to notify the designated MOH officers in real-time so they are equipped with information to take immediate action. mSOS also sends mass SMS to relay important disease surveillance and response information, such as case definitions and isolation measures, to mSOS-registered users.
Electrical Wiring: Electrical circuits wiring tutorial
 
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This Electrical wiring video by http://www.bin95.com shows how to modify an existing motor circuit's electrical wiring using a motor control diagram. This electrical wiring tutorial video is one of the many electrical circuits explored in DVD 4 of the 10 DVD Industrial Electrical Training Video Library. http://www.youtube.com/watch?v=9uMIQycxygQ
Views: 988341 BIN Industrial Training
Data mining | Wikipedia audio article
 
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This is an audio version of the Wikipedia Article: https://en.wikipedia.org/wiki/Data_mining 00:03:56 1 Etymology 00:06:57 2 Background 00:08:33 3 Process 00:10:12 3.1 Pre-processing 00:11:02 3.2 Data mining 00:12:47 3.3 Results validation 00:15:13 4 Research 00:16:34 5 Standards 00:17:59 6 Notable uses 00:18:23 7 Privacy concerns and ethics 00:21:38 7.1 Situation in Europe 00:22:24 7.2 Situation in the United States 00:23:57 8 Copyright law 00:24:07 8.1 Situation in Europe 00:25:48 8.2 Situation in the United States 00:26:43 9 Software 00:26:52 9.1 Free open-source data mining software and applications 00:29:55 9.2 Proprietary data-mining software and applications 00:31:54 9.3 Marketplace surveys 00:33:36 10 See also Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago. Learning by listening is a great way to: - increases imagination and understanding - improves your listening skills - improves your own spoken accent - learn while on the move - reduce eye strain Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone. Listen on Google Assistant through Extra Audio: https://assistant.google.com/services/invoke/uid/0000001a130b3f91 Other Wikipedia audio articles at: https://www.youtube.com/results?search_query=wikipedia+tts Upload your own Wikipedia articles through: https://github.com/nodef/wikipedia-tts Speaking Rate: 0.8650267505126996 Voice name: en-US-Wavenet-F "I cannot teach anybody anything, I can only make them think." - Socrates SUMMARY ======= Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The difference between data analysis and data mining is that data analysis is to summarize the history such as analyzing the effectiveness of a marketing campaign, in contrast, data mining focuses on using specific machine learning and statistical models to predict the future and discover the patterns among data.The term "data mining" is in fact a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself. It also is a buzzword and is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence (e.g., machine learning) and business intelligence. The book Data mining: Practical machine learning tools and techniques with Java (which covers mostly machine learning material) was originally to be named just Practical machine learning, and the term data mining was only added for marketing reasons. Often the more general terms (large scale) data analysis and analytics – or, when referring to actual methods, artificial intelligence and machine learning – are more appropriate. The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining, sequential pattern mining). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, but do belong to the overall KDD process as additional steps. The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be ...
Views: 2 wikipedia tts
FITMAN SE Metadata Ontologies Semantic Matching
 
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FITMAN FI-PPP Phase II Project - Sotiris Koussouris (National Technical University of Athens - NTUA) Presenting Metadata Ontologies Semantic Matching Specific Enabler (SE)
Views: 175 FITMAN FI
Business Understanding
 
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Animated Video created using Animaker - https://www.animaker.com Bana
Views: 20 Niko Muñoz
Managing the Analytics Life Cycle
 
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Successful organizations recognize that analytic models are essential corporate assets that produce and deliver answers to production systems for improved customer relationships, improved operations, increased revenues and reduced risks. So, they seek to create the best models possible. However, few fully manage all the complexities of the complete analytical model life cycle. It’s such a multifaceted task. Therefore, it is important to develop an iterative analytics life cycle to guide organization step-by-step through the process of going from data to decision. In order to provide a framework to organize the work needed by an organization and deliver clear insights from Big Data, it’s useful to think of it as a cycle with different stages.
Views: 673 Chee-Onn Leong
TechBytes - The Process of Data Science and Teradata Vantage
 
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This TechBytes walks you through the 5 key steps within the process of data science. See how Teradata Vantage and its rich set of functions enable each of the process steps while allowing data scientists to use their favorite analytic tools and languages and to access variety of data sources.
Views: 1032 Teradata
What is Data Entry in Hindi
 
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here subject is what is data entry in hindi. A data entry work is similar job to a typist in which data entry staff employed to enter or update data into a computer system database, often from paper documents using a keyboard, optical scanner, or data recorder.The keyboards used can often have specialist keys and multiple colors to help in the task and speed up the work. While requisite skills can vary depending on the nature of the data being entered, few specialized skills are usually required, aside from touch typing proficiency with adequate speed and accuracy. The ability to focus for lengthy periods is necessary to eliminate or at least reduce errors. When dealing with sensitive or private information such as medical, financial or military records, a person's character and discretion becomes very relevant as well. Beyond these traits, no technical knowledge is generally required and these jobs can even be worked from home. The invention of punch card data processing in the 1890's created a demand for many workers, typically women, to run key-punch machines. It was common practice to ensure accuracy by entering data twice, the second time on a verifier, a separate, keyboard-equipped machine, such the IBM 056. In the 1970's, punch card data entry was gradually replaced by the use of video display terminals. Reference:-https://en.wikipedia.org/wiki/Data_entry_clerk Reference:-https://www.upwork.com/ Subscribe:- goo.gl/9TVZ3I Watch How To Type Fast in Just 3 Weeks :- https://youtu.be/HE-3bpYvGc4 Check my Google plus :- https://plus.google.com/+Introtuts
Views: 624644 Introtuts
A Two-Stage Hybrid Model by Using Artificial Neural Networks as Feature Construction Algorithms
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] ABSTRACT We propose a two-stage hybrid approach with neural networks as the new feature construction algorithms for bankcard response classifications. The hybrid model uses a very simpleneural network structure as the new feature construction tool in the firststage, thenthe newly created features are used asthe additional input variables in logistic regression in the second stage. The modelis compared with the traditional onestage model in credit customer response classification. It is observed that the proposed two-stage model outperforms the one-stage model in terms of accuracy, the area under ROC curve, andKS statistic. By creating new features with theneural network technique, the underlying nonlinear relationships between variables are identified. Furthermore, by using a verysimple neural network structure, the model could overcome the drawbacks of neural networks interms of its long training time, complex topology, and limited interpretability.
Views: 12 aircc journal
Accounting Basics Class - 1 (In Kannada - ಕನ್ನಡದಲ್ಲಿ)
 
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Please watch: "Accounting Basics & Tally Class - 4 (In Kannada - ಕನ್ನಡದಲ್ಲಿ)" https://www.youtube.com/watch?v=G-n47ISPLpw -~-~~-~~~-~~-~- Learn Accounting Basics in Kannada. (ಕನ್ನಡದಲ್ಲಿ Accounting Basics ಕಲಿಯಿರಿ)
Views: 236795 Yuvaraj Madha
HUG Meetup October 2012: Apache Accumulo: Unlocking the Power of Big Data (Part I)
 
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Presenter: Adam Fuchs, CTO, sqrrl Apache Accumulo, originally developed by the National Security Agency and now an Apache Software Foundation project, builds upon Google's Bigtable design to provide a scalable, lightly-structured database capability complementing the ubiquitous Hadoop environment. The core capabilities of Accumulo include cell-level security, flexible schemas, real-time analytics, bulk I/O, and linear scalability beyond trillions of entries and petabytes of data. These new capabilities lead to techniques that unlock the power of Big Data, but don't fit into traditional database design patterns. Learn about the advantages of Apache Accumulo and how it fits into the Hadoop and NoSQL ecosystem.
Views: 874 ydntheater
IEEE 2017-2018 DATA MINING PROJECTS A SCALABLE AND COOPERATIVE MAC
 
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PG Embedded Systems #197 B, Surandai Road Pavoorchatram,Tenkasi Tirunelveli Tamil Nadu India 627 808 Tel:04633-251200 Mob:+91-98658-62045 General Information and Enquiries: [email protected] [email protected] PROJECTS FROM PG EMBEDDED SYSTEMS 2017 ieee projects, 2017 ieee java projects, 2017 ieee dotnet projects, 2017 ieee android projects, 2017 ieee matlab projects, 2017 ieee embedded projects, 2017 ieee robotics projects, 2017 IEEE EEE PROJECTS, 2017 IEEE POWER ELECTRONICS PROJECTS, ieee 2017 android projects, ieee 2017 java projects, ieee 2017 dotnet projects, 2017 ieee mtech projects, 2017 ieee btech projects, 2017 ieee be projects, ieee 2017 projects for cse, 2017 ieee cse projects, 2017 ieee it projects, 2017 ieee ece projects, 2017 ieee mca projects, 2017 ieee mphil projects, tirunelveli ieee projects, best project centre in tirunelveli, bulk ieee projects, pg embedded systems ieee projects, pg embedded systems ieee projects, latest ieee projects, ieee projects for mtech, ieee projects for btech, ieee projects for mphil, ieee projects for be, ieee projects, student projects, students ieee projects, ieee proejcts india, ms projects, bits pilani ms projects, uk ms projects, ms ieee projects, ieee android real time projects, 2017 mtech projects, 2017 mphil projects, 2017 ieee projects with source code, tirunelveli mtech projects, pg embedded systems ieee projects, ieee projects, 2017 ieee project source code, journal paper publication guidance, conference paper publication guidance, ieee project, free ieee project, ieee projects for students., 2017 ieee omnet++ projects, ieee 2017 oment++ project, innovative ieee projects, latest ieee projects, 2017 latest ieee projects, ieee cloud computing projects, 2017 ieee cloud computing projects, 2017 ieee networking projects, ieee networking projects, 2017 ieee data mining projects, ieee data mining projects, 2017 ieee network security projects, ieee network security projects, 2017 ieee image processing projects, ieee image processing projects, ieee parallel and distributed system projects, ieee information security projects, 2017 wireless networking projects ieee, 2017 ieee web service projects, 2017 ieee soa projects, ieee 2017 vlsi projects, NS2 PROJECTS,NS3 PROJECTS. DOWNLOAD IEEE PROJECTS: 2017 IEEE java projects,2017 ieee Project Titles, 2017 IEEE cse Project Titles, 2017 IEEE NS2 Project Titles, 2017 IEEE dotnet Project Titles.
Views: 17 ganesh pg
How to Make a Simple Metal Detector
 
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This tutorial will show you how to make a metal detector circuit with a few electronic parts.
Views: 243897 Ludic Science
Tally erp 9 Inventory Vouchers with Live Practical on Actual Data.
 
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Learn Inventory Accounting with Practical Project in Tally Erp 9. Practical class in hindi by City Commerce Academy. Lecture by Prof. Amar Jeet Singh. Other Class is also available on : Basic Accounts, Manual Accounts, Compute Accounts, Tally erp 9 , Balance Sheet, Inventory Accounts, Reconciliations, Vat, Sales Tax, Service Tax, Income Tax, TDS, Excise, EPF, ESI etc.
Views: 1246551 Amar Jeet Singh
Barbara Block, Kyle Van Houtan, et al: "Fixing the Engine that Powers the Planet" | Talks at Google
 
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We are connected to the world through modern technology networks, but as human beings, we are connected to one another by an ancient network that powers quite literally the entire planet: the ocean. This vast ecosystem is currently at risk, and if we are to protect it, we first need to understand our connection to it. This panel explores the ways in which our consumption and economic activities impact the oceans, the unintended and strangely interconnected consequences of those patterns and activities, and what we can all do as people and employees to turn things around. Panelists (left to right): Ana Blanco Dr. Kyle S. Van Houtan Dr. Barbara Block David Helvarg Birgitte Rasine Moderated by Michiel Bakker. Get the book: https://goo.gl/ZW5k3U
Views: 1493 Talks at Google
Final Year Projects | Ontology Matching: State of t he Artand Future Challenges
 
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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:+91 967-778-1155 +91 958-553-3547 +91 967-774-8277 Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected] chat: http://support.elysiumtechnologies.com/support/livechat/chat.php
Views: 165 myproject bazaar
L7/P2: Infrastructure-Railways, aviation and shipping, Bibek Debroy Rail Restructuring
 
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Language: Hindi, Topics Covered: 1. Indian Railways: study topics for India 2015 yearbook 2. Rail budget 2015: salient features and targets 3. comparison between Indian Railways and Chinese railways 4. Rail reforms: Kayakalp council 5. Rail reforms: Bibek Debroy Committee- major recommendations- human resource management, focus on core activities, independent body for ticket pricing, joint venture with state governments for suburban railways, merger of rail ministry with transport Ministry, merger of real budget with general budget and separate committee for investment. 6. The benefits of transporting men and material through railways 7. Mock Question for Mains: Public investment, especially in the railways, can play an important role to revive growth and promote Make in India. Discuss 8. Aviation: Self study topics from India yearbook, Draft civil aviation policy 2014: salient features of, No frills airports 9. Shipping: self study topics from India yearbook, positive and negative points about Indian shipping industry, reforms initiated in recent years, Sagar mala vs. Sethu Samudram Powerpoint available at http://Mrunal.org/download Exam-Utility: UPSC CSAT, Prelims, Mains, CDS, CAPF, Bank, RBI, IBPS, SSC and other competitive exams, IIM, XLRI, MBA interviews and GDPI Faculty Name: Mrunal Patel Venue: Sardar Patel Institute of Public Administration (SPIPA), Satellite, Ahmedabad, Gujarat,India
Views: 36212 Mrunal Patel
NEO DevCon 2019 DAY 1 Live Streaming 2019/02/16
 
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NEO DevCon 2019 DAY 1 Live Streaming 2019/02/16 Timestamps: 6:42 The Promise of the Smart Economy - Da Hongfei, Founder 42:35 Possible Improvements in NEO 3.0 - Erik Zhang, Founder 1:04:25 NEO Global Growth - Zhao Chen, General Manager, NGD --- Break --- 1:44:44 Blockchain for Digital Transformation - Drew Gude, Managing Director, Microsoft Digital Worldwide 2:06:48 Big Trend in Blockchain - Miha Kralj, Managing Director, Accenture 2:23:42 Regulator’s Perspective in Blockchain - Dr. Joseph Williams, ICT Industry Sector Lead 2:37:00 Blockchain Use Cases and Enterprise Needs on the Microsoft Platform - Pablo Junco, Director, Worldwide Apps Solutions Strategy, Microsoft --- Break --- 4:01:43 NEO Protocol Quality Assurance - Peter Lin, R&D Director, NGD 4:23:35 NEO Developer Guide - Longfei Wang - Software Developer, NGD 4:35:25 Seraph ID – Self-sovereign Identity on NEO - Waldemar Scherer, Head of Enterprise Blockchain 4:54:50 Panel: About Decentralization - Waldemar Scherer; Fabio C.Canesin; Peter Lin; Douwe van de Ruit 5:18:00 Many Ways to Double Spend Your Cryptocurrency - Dr. Zhiniang Peng, Security Researcher, Qihoo 360 5:34:40 Building Trustworthy Blockchain Ecosystems - Dr. Ronghui Gu, Certik, CEO 6:09:51 XLang - Harry Pierson, Program Manager for Xlang, Microsoft 6:30:08 Panel: How to Expand Developer Communities - Brett Rhodes ("Edgegasm") et al. 6:55:00 Cryptoeconomics and the Future of the Global Economy - Dr. Chris Berg, Senior Research fellow, RMIT 7:12:40 NEO.GAME - Blockchain Game One Stop Solution - John Wang, Ecosystem Growth Manager, NGD 7:26:52 NEO Friends Initiative - Tamar Salant, Ecosystem Growth Manager, NGD For more info, please visit: https://devcon.neo.org/
Views: 9746 NEO Smart Economy
NIPS 2011 Learning Semantics Workshop: Towards More Human-like Machine Learning of Word Meanings
 
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Learning Semantics Workshop at NIPS 2011 Invited Talk: Towards More Human-like Machine Learning of Word Meanings by Josh Tenenbaum Josh Tenenbaum is a Professor in the Department of Brain and Cognitive Sciences at Massachusetts Institute of Technology. Him and his colleagues in the Computational Cognitive Science group study one of the most basic and distinctively human aspects of cognition: the ability to learn so much about the world, rapidly and flexibly. Abstract: How can we build machines that learn the meanings of words more like the way that human children do? I will talk about several challenges and how we are beginning to address them using sophisticated probabilistic models. Children can learn words from minimal data, often just one or a few positive examples (one-shot learning). Children learn to learn: they acquire powerful inductive biases for new word meanings in the course of learning their first words. Children can learn words for abstract concepts or types of concepts that have no little or no direct perceptual correlate. Children's language can be highly context-sensitive, with parameters of word meaning that must be computed anew for each context rather than simply stored. Children learn function words: words whose meanings are expressed purely in how they compose with the meanings of other words. Children learn whole systems of words together, in mutually constraining ways, such as color terms, number words, or spatial prepositions. Children learn word meanings that not only describe the world but can be used for reasoning, including causal and counterfactual reasoning. Bayesian learning defined over appropriately structured representations — hierarchical probabilistic models, generative process models, and compositional probabilistic languages — provides a basis for beginning to address these challenges.
Views: 2540 GoogleTechTalks
Finance vs Consulting | Which Career to Choose?
 
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In this video on Finance vs Consulting, we will do the analysis between a finance guy and a consultant. 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐁𝐞𝐭𝐰𝐞𝐞𝐧 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠 ---------------------------------------------------------------------------- The one and only difference in finance and consulting is that the compensation. You would earn a little bit more while starting your Finance career than starting your management consulting career. But if you stick to your laurel, if you will do well, you will earn much more as a management consultant than a finance professional. 𝐂𝐚𝐫𝐞𝐞𝐫𝐬 𝐢𝐧 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 --------------------------------- 1. Technical analysis 2. Corporate Finance Equity Research 3. Risk Management 4. Private Equity 5. Investment Banking 6. Project Finance 7. Equity Research 8. Quantitative Analysis 𝐂𝐚𝐫𝐞𝐞𝐫 𝐎𝐩𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠 -------------------------------------------------- 1. Management Consulting 2. IT Consulting and other areas 3. Strategic Consulting 𝐒𝐤𝐢𝐥𝐥𝐬 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐢𝐧 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 ---------------------------------------------- 1. Accounting 2. Microsoft Excel 3. Valuation Methods 4. PowerPoint 5. Corporate Finance 6. Fixed Income 7. Financial Modeling 8. Corporate Law 9. Derivatives 𝐒𝐤𝐢𝐥𝐥𝐬 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐝 𝐢𝐧 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠 --------------------------------------------------- 1. Analytical Skills 2. Operations 3. Business Modeling 4. Microsoft PowerPoint (heavy) 5. Microsoft Excel (less) 6. Business Strategy 7. Human Resource 8. Supply Chain 9. Process vast data 𝐇𝐨𝐰 𝐓𝐨 𝐆𝐞𝐭 𝐈𝐧𝐭𝐨 𝐚 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 𝐑𝐨𝐥𝐞? -------------------------------------------------------- The 1st step is to decide what you want to specialize in. Is it something that you want to do at least for the next 10-15 years? If yes, then choose whatever speaks to you. 𝐇𝐨𝐰 𝐓𝐨 𝐆𝐞𝐭 𝐈𝐧𝐭𝐨 𝐚 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠 𝐑𝐨𝐥𝐞? ------------------------------------------------------------- You can join a big consulting firm like McKinsey & Company, Boston Consulting Group, Bain & Company, Accenture etc and can learn the art of the trade. To know more about Finance vs Consulting, you can go to this 𝐥𝐢𝐧𝐤 𝐡𝐞𝐫𝐞: https://www.wallstreetmojo.com/Finance-vs-Consulting/ Subscribe to our channel to get new updated videos.Click the button above to subscribe or click on link below to subscribe - https://www.youtube.com/channel/UChlNXSK2tC9SJ2Fhhb2kOUw?sub_confirmation=1
Views: 2473 WallStreetMojo
Deaf since birth, artist Christine Sun Kim explores the social rules of sound
 
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Christine Sun Kim is a sound artist who has been deaf since birth. Art Beat met up with her at Artisphere in Virginia to learn more about her installations and her explorations of the social rules governing sound. For more Art Beat: http://www.newshour.pbs.org/art
Views: 5869 PBS NewsHour
A Lei da Água - Filme Completo
 
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“A Lei da Água (Novo Código Florestal)” esclarece as mudanças promovidas pelo novo Código Florestal e a polêmica sobre a sua elaboração e implantação. O documentário mostra como a lei impacta diretamente a floresta e, assim, a água, o ar, a fertilidade do solo, a produção de alimentos e a vida de cada cidadão. Produzida ao longo de 16 meses, a obra baseia-se em pesquisa e 37 entrevistas com ambientalistas, ruralistas, cientistas e agricultores. Retrata ainda casos concretos de degradação ambiental e técnicas agrícolas sustentáveis que podem conciliar os interesses de conservação e produção da sociedade. "The Water Law" explains the changes introduced by the new Forest Code and the controversy over its design and implementation. The documentary shows how the law directly impacts the forest and thus the water, air, soil fertility, food production and the life of every citizen. Produced over 16 months, the work is based on a research and interviews with 37 environmental, scientists and farmers. The documentary also portrays individual cases of environmental degradation and sustainable agricultural techniques that can reconcile the interests of conservation and production of society.
Views: 221851 O2 Play Filmes
Common Core Revolution
 
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'The Revolution Band' from Massachusetts perform "Common Core Revolution". Original music by The Beatles (duh) ... we're not selling this, just using it to promote Common Core awareness (lyrics below). Please sign our ballot initiative to END COMMON CORE here: http://www.endcommoncorema.com/ Lyrics: We say we want a Revolution Well you know, we all hate Common Core You tell me it's a school solution Well you know, it makes a parent go to war And when you take away democracy, Don't you know that you can count me out! Well we have to tell the Feds, it's not all right... Politicians fear no retribution Well you know, we're all going to vote them out 'Race to The Top' is no contribution, Well you know, control and money's what is what its about If you want math and tests we really hate, No art and music makes us really irate Well we have to tell the Feds, it's not all right... You'd have to change the Constitution Well you know, you just spit on it instead Teachers have no say in education Well you know, schools should be state led But if you go carrying pictures of Bill gates The 99% better change our fate Well we have to tell the Feds, it's not all right...
Views: 4820 Mike Gioscia