RapidMiner PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download RapidMiner PDF full book. Access full book title RapidMiner by Markus Hofmann. Download full books in PDF and EPUB format.
Author: Markus Hofmann
Publisher: CRC Press
ISBN: 1482205505
Category : Business & Economics
Languages : en
Pages : 518
Get Book Here
Book Description
Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today's world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of incre
Author: Markus Hofmann
Publisher: CRC Press
ISBN: 1482205505
Category : Business & Economics
Languages : en
Pages : 518
Get Book Here
Book Description
Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today's world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of incre
Author: Vijay Kotu
Publisher: Morgan Kaufmann
ISBN: 0128016507
Category : Computers
Languages : en
Pages : 447
Get Book Here
Book Description
Put Predictive Analytics into ActionLearn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to:1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples
Author: Ramjan, Sarawut
Publisher: IGI Global
ISBN: 1668447320
Category : Computers
Languages : en
Pages : 326
Get Book Here
Book Description
The demand for skilled data scientists is rapidly increasing as more organizations recognize the value of data-driven decision- making. Data science, data management, and data mining are all critical components for various types of organizations, including large and small corporations, academic institutions, and government entities. For companies, these components serve to extract insights and value from their data, empowering them to make evidence-driven decisions and gain a competitive advantage by discovering patterns and trends and avoiding costly mistakes. Academic institutions utilize these tools to analyze large datasets and gain insights into various scientific fields of study, including genetic data, climate data, financial data, and in the social sciences they are used to analyze survey data, behavioral data, and public opinion data. Governments use data science to analyze data that can inform policy decisions, such as identifying areas with high crime rates, determining which regions need infrastructure development, and predicting disease outbreaks. However, individuals who are not data science experts, but are experts within their own fields, may need to apply their experience to the data they must manage, but still struggle to expand their knowledge of how to use data mining tools such as RapidMiner software. Principles and Theories of Data Mining With RapidMiner is a comprehensive guide for students and individuals interested in experimenting with data mining using RapidMiner software. This book takes a practical approach to learning through the RapidMiner tool, with exercises and case studies that demonstrate how to apply data mining techniques to real-world scenarios. Readers will learn essential concepts related to data mining, such as supervised learning, unsupervised learning, association rule mining, categorical data, continuous data, and data quality. Additionally, readers will learn how to apply data mining techniques to popular algorithms, including k-nearest neighbor (K-NN), decision tree, naïve bayes, artificial neural network (ANN), k-means clustering, and probabilistic methods. By the end of the book, readers will have the skills and confidence to use RapidMiner software effectively and efficiently, making it an ideal resource for anyone, whether a student or a professional, who needs to expand their knowledge of data mining with RapidMiner software.
Author: Kris Jamsa
Publisher: Jones & Bartlett Learning
ISBN: 1284180905
Category : Computers
Languages : en
Pages : 687
Get Book Here
Book Description
Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.
Author: Richard J. Roiger
Publisher: CRC Press
ISBN: 1498763987
Category : Business & Economics
Languages : en
Pages : 530
Get Book Here
Book Description
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/
Author: Matthew North
Publisher:
ISBN: 9781727102475
Category :
Languages : en
Pages : 310
Get Book Here
Book Description
Some say we live in the Information Age; others, the Social Age; and still others, the Big Data Age. Regardless of what name we give it, we live in an age that generates monumental amounts of data-in all different kinds of formats. In business, and in our personal lives, we use smartphones and tablets, web sites and watches; with apps and interfaces to shop, learn, entertain and inform. Businesses increasingly use technology to interact with consumers to provide marketing, customer service, product information and more. All of this technological activity generates data, and we're increasingly good at gathering, storing and analyzing it.Data mining can help to identify interesting patterns and messages that exist in data, often hidden beneath the surface. In this modern age of information systems, it is easier than ever before to extract meaning from data. From classification to prediction, data mining can help.In Data Mining for the Masses, Third Edition, professor Matt North-a former risk analyst and software engineer at eBay-uses simple examples and clear explanations with free, powerful software tools to teach you the basics of data mining. In this Third Edition, implementations of these examples are offered in current versions of the RapidMiner software, and in the increasingly popular R Statistical Package.You've got more data than ever before and you know it's got value, if only you can figure out how to get to it. This book can show you how. Let's start digging!
Author: Vijay Kotu
Publisher: Morgan Kaufmann
ISBN: 0128147628
Category : Computers
Languages : en
Pages : 570
Get Book Here
Book Description
Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: - Gain the necessary knowledge of different data science techniques to extract value from data. - Master the concepts and inner workings of 30 commonly used powerful data science algorithms. - Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... - Contains fully updated content on data science, including tactics on how to mine business data for information - Presents simple explanations for over twenty powerful data science techniques - Enables the practical use of data science algorithms without the need for programming - Demonstrates processes with practical use cases - Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language - Describes the commonly used setup options for the open source tool RapidMiner
Author: Zara Mareuwine
Publisher: ZM Publication
ISBN:
Category : Reference
Languages : en
Pages : 51
Get Book Here
Book Description
ChatGPT prompts coverage: Reference management software: Zotero, Mendeley, and EndNote Data analysis software: SPSS, R, Stata, Atlas.ti, NVivo Writing and publishing software: Microsoft Word, LaTeX, Google Docs arXiv, SSRN, and ResearchGate Collaboration and communication tools: Slack, Microsoft Teams, and Zoom Note-taking software: Evernote, OneNote, and Notion Mind-mapping software: MindNode, XMind, and FreeMind Reference search engines: Google Scholar, Web of Science, and Scopus Project management software: Trello, Asana, and Jira Data visualization software: Tools such as Tableau, Plotly, and D3.js Text mining and natural language processing tools: NLTK, OpenNLP, and RapidMine
Author: Dr. Eng. Imam Tahyudin, MM
Publisher: Zahira Media Publisher
ISBN: 6230954028
Category : Computers
Languages : en
Pages : 315
Get Book Here
Book Description
This textbook discusses the Problems in Big Data, Big Data Characteristics, Map Reduce Paradigm in Big Data, Various tools used in Big Data, examples of the application of Big Data and Analytics. Related courses / RPS)
Author: Suresh Chandra Satapathy
Publisher: Springer
ISBN: 3030243222
Category : Technology & Engineering
Languages : en
Pages : 838
Get Book Here
Book Description
This book constitutes the proceedings of the First International Conference on Emerging Trends in Engineering (ICETE), held at University College of Engineering and organised by the Alumni Association, University College of Engineering, Osmania University, in Hyderabad, India on 22–23 March 2019. The proceedings of the ICETE are published in three volumes, covering seven areas: Biomedical, Civil, Computer Science, Electrical & Electronics, Electronics & Communication, Mechanical, and Mining Engineering. The 215 peer-reviewed papers from around the globe present the latest state-of-the-art research, and are useful to postgraduate students, researchers, academics and industry engineers working in the respective fields. Volume 1 presents papers on the theme “Advances in Decision Sciences, Image Processing, Security and Computer Vision – International Conference on Emerging Trends in Engineering (ICETE)”. It includes state-of-the-art technical contributions in the area of biomedical and computer science engineering, discussing sustainable developments in the field, such as instrumentation and innovation, signal and image processing, Internet of Things, cryptography and network security, data mining and machine learning.
