Download or read book Java Data Mining A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-05-18 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is it economical; do you have the time and money? What stupid rule would you most like to kill? How is progress measured? Is the required Java Data Mining data gathered? Who will be responsible for making the decisions to include or exclude requested changes once Java Data Mining is underway? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Java Data Mining investments work better. This Java Data Mining All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Java Data Mining Self-Assessment. Featuring 949 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Java Data Mining improvements can be made. In using the questions you will be better able to: - diagnose Java Data Mining projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Java Data Mining and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Java Data Mining Scorecard, you will develop a clear picture of which Java Data Mining areas need attention. Your purchase includes access details to the Java Data Mining self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Java Data Mining Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Download or read book Data Mining A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining A Complete Guide - 2020 Edition.
Download or read book Java Data Mining The Ultimate Step By Step Guide written by Gerardus Blokdyk and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Java Data Mining The Ultimate Step-By-Step Guide.
Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Download or read book Java Data Mining Strategy Standard and Practice written by Mark F. Hornick and published by Elsevier. This book was released on 2010-07-26 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems JDM essentials - concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects JDM in practice - the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API Free, downloadable KJDM source code referenced in the book available here
Download or read book Java Data Mining the Ultimate Step By Step Guide written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2018-04-13 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are our Java Data Mining Processes? How does Java Data Mining integrate with other business initiatives? Which customers cant participate in our Java Data Mining domain because they lack skills, wealth, or convenient access to existing solutions? What business benefits will Java Data Mining goals deliver if achieved? Why are Java Data Mining skills important? This valuable Java Data Mining self-assessment will make you the principal Java Data Mining domain auditor by revealing just what you need to know to be fluent and ready for any Java Data Mining challenge. How do I reduce the effort in the Java Data Mining work to be done to get problems solved? How can I ensure that plans of action include every Java Data Mining task and that every Java Data Mining outcome is in place? How will I save time investigating strategic and tactical options and ensuring Java Data Mining costs are low? How can I deliver tailored Java Data Mining advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Java Data Mining essentials are covered, from every angle: the Java Data Mining self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Java Data Mining outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Java Data Mining practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Java Data Mining are maximized with professional results. Your purchase includes access details to the Java Data Mining self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book.
Download or read book Data Mining A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-09-19 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are the leading papers around models for quantifying the quality of judges in crowdsourcing? What error rate, on future unseen data, would you expect from a predictive classification model you have built using a given training set? How do you cover the basic algorithms regarding semantics grammar sentence splitting etc? What are the pros and cons of outsourcing business intelligence? What are the differences between visual data mining and data visualization? This breakthrough Data Mining self-assessment will make you the assured Data Mining domain adviser by revealing just what you need to know to be fluent and ready for any Data Mining challenge. How do I reduce the effort in the Data Mining work to be done to get problems solved? How can I ensure that plans of action include every Data Mining task and that every Data Mining outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Mining costs are low? How can I deliver tailored Data Mining advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Mining essentials are covered, from every angle: the Data Mining self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Mining outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Mining practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Mining are maximized with professional results. Your purchase includes access details to the Data Mining self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Mining Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Download or read book A Quick Guide to Data Mining with Weka and Java using Weka written by Eric Goh and published by SVBook. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This technical book aim to equip the reader with Weka, Data Mining in a fast and practical way. There will be many examples and explanations that are straight to the point. Contents 1. Introduction (What is data science, what is data mining, CRISP DM Model, what is text mining, three types of analytics, big data) 2. Getting Started (INstall Weka) 3. Prediction and Classification (Prediction and Classification) 4. Machine Learning Basics (KMeans Clustering, Decision Tree, Naive Bayes, KNN, Neural Network) 5. Data Mining with Weka (Data Understanding using Weka, Data Preparation using Weka, Model Building and Evaluation using Weka) 6. Java interact Weka (Use Java to use Weka, in order to develop your own prediction or classification system) 7. Conclusion This book has been taught at Udemy and EMHAcademy.com. Use the following Coupon to get the Udemy Course at $11.99: https://www.udemy.com/machine-learning-with-java-and-weka/?couponCode=SPECIALCOUPON
Download or read book Data Mining written by Ian H. Witten and published by Morgan Kaufmann. This book was released on 2016-10-01 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at https://www.cs.waikato.ac.nz/~ml/weka/book.html. It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface Includes open-access online courses that introduce practical applications of the material in the book
Download or read book Data Mining written by Ian H. Witten and published by Morgan Kaufmann. This book was released on 2000 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.
Download or read book Data Mining And Knowledge Discovery A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-03 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does your signature ensure? Who is involved with workflow mapping? How do you set Data Mining and Knowledge Discovery stretch targets and how do you get people to not only participate in setting these stretch targets but also that they strive to achieve these? Can you break it down? Do the benefits outweigh the costs? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Mining And Knowledge Discovery investments work better. This Data Mining And Knowledge Discovery All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data Mining And Knowledge Discovery Self-Assessment. Featuring 946 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Mining And Knowledge Discovery improvements can be made. In using the questions you will be better able to: - diagnose Data Mining And Knowledge Discovery projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data Mining And Knowledge Discovery and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data Mining And Knowledge Discovery Scorecard, you will develop a clear picture of which Data Mining And Knowledge Discovery areas need attention. Your purchase includes access details to the Data Mining And Knowledge Discovery self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Mining And Knowledge Discovery Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Download or read book A Practical Guide to Data Mining for Business and Industry written by Andrea Ahlemeyer-Stubbe and published by John Wiley & Sons. This book was released on 2014-03-31 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
Download or read book Data Mining written by Richard J. Roiger and published by CRC Press. This book was released on 2017-01-06 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides in-depth coverage of basic and advanced topics in data mining and knowledge discovery Presents the most popular data mining algorithms in an easy to follow format Includes instructional tutorials on applying the various data mining algorithms Provides several interesting datasets ready to be mined Offers in-depth coverage of RapidMiner Studio and Weka’s Explorer interface Teaches the reader (student,) hands-on, about data mining using RapidMiner Studio and Weka Gives instructors a wealth of helpful resources, including all RapidMiner processes used for the tutorials and for solving the end of chapter exercises. Instructors will be able to get off the starting block with minimal effort Extra resources include screenshot sequences for all RapidMiner and Weka tutorials and demonstrations, available for students and instructors alike The latest version of all freely available materials can also be downloaded at: http://krypton.mnsu.edu/~sa7379bt/
Download or read book Learn By Examples A Quick Guide to Data Mining with RapidMiner and Weka written by Eric Goh and published by SVBook Pte. Ltd. . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aim to equip the reader with RaidMiner and Weka and Data Mining basics. There will be many examples and explanations that are straight to the point. You will be walked through data mining process from data preparation to data analysis (descriptive statistics) and data visualization to prediction modeling (machine learning) using Weka and RapidMiner. Content Covered: - Introduction (What is data science, what is data mining, CRISP DM Model, what is text mining, three types of analytics, big data) - Getting Started (INstall Weka and RapidMiner) - Prediction and Classification (Prediction and Classification) - Machine Learning Basics (Kmeans Clustering, Decision Tree, Naive Bayes, KNN, Neural Network) - Data Mining with Weka (Data Understanding using Weka, Data Preparation using Weka, Model Building and Evaluation using Weka) - Data Mining with RapidMiner (Data Understanding using RapidMiner, Data Preparation using RapidMiner, Model Building and Evaluation using RapidMiner) - Conclusion We will be using opensource tools, hence, you don't have to worry about buying any softwares. The book is designed for non-programmers only. It will gives you a head start into Weka and RapidMiner, with a touch on data mining. This book has been taught at Udemy and EMHAcademy.com. Use the following Coupon to get the Udemy Course at $11.99: https://www.udemy.com/data-mining-with-rapidminer/?couponCode=EBOOKSPECIAL https://www.udemy.com/learn-machine-learning-with-weka/?couponCode=EBOOKSPECIAL
Download or read book Data Mining written by Liam Damien and published by . This book was released on 2019-12-02 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you think there are shortcuts to data mining, then think again! So many people today think that data mining has the ability to sail away from every data storm. The truth is, it will not!When you realize that you are struggling to improve the accuracy of models, only then can you employ the use of data mining techniques for your rescue. Personally, I have been through the same situations many times. When I first started out as a business analytics personnel, my mentor suggested that I spend a lot of time data mining and doing data analysis. Well, I can't thank him enough for that piece of advice. Today, we live in the age of massive production of data. Machines and platforms are churning out data like never before! Start by taking count of the number of gadgets you have. How many services have you signed up for? Facebook, Instagram, Uber, Twitter, E-commerce - the list is endless. What is interesting is that all this data goes right back to whoever owns the product. They then use that information to improve their products. It is this process of gathering data that is referred to as Data Mining. What you need to understand is that the more data you collect, the more value you can deliver. The more value you provide, the more revenue your business generates. Here, we will discuss what data mining is all about and how you can use that data to make a lot of difference in your business and the world around you.Come with me and let's get down to work!
Download or read book Programming for Data Science written by Erick Thompson and published by . This book was released on 2020-12-21 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Predictive Data Mining written by Sholom M. Weiss and published by Morgan Kaufmann. This book was released on 1998 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical guide to provide a complete, generalized road map for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.
