rapidminer

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Rapidminer

Author : Markus Hofmann
ISBN : 9781482205503
Genre : Business & Economics
File Size : 34. 45 MB
Format : PDF
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Powerful, Flexible Tools for a Data-Driven World As 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 increasingly complex problems. Learn from the Creators of the RapidMiner Software Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com. Understand Each Stage of the Data Mining Process The book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining. Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.

Learn By Examples A Quick Guide To Data Mining With Rapidminer And Weka

Author : Eric Goh
ISBN :
Genre : Business & Economics
File Size : 31. 52 MB
Format : PDF, ePub, Mobi
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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

Predictive Analytics And Data Mining

Author : Vijay Kotu
ISBN : 9780128016503
Genre : Computers
File Size : 54. 64 MB
Format : PDF, ePub, Docs
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Put Predictive Analytics into Action Learn 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

Exploring Data With Rapidminer

Author : Andrew Chisholm
ISBN : 9781782169345
Genre : Computers
File Size : 46. 87 MB
Format : PDF, Docs
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A step-by-step tutorial style using examples so that users of different levels will benefit from the facilities offered by RapidMiner.If you are a computer scientist or an engineer who has real data from which you want to extract value, this book is ideal for you. You will need to have at least a basic awareness of data mining techniques and some exposure to RapidMiner.

Rapidminer Second Edition

Author : Markus Hofmann
ISBN : 1138197009
Genre :
File Size : 78. 42 MB
Format : PDF, Docs
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Written by leaders in the data mining community, including the developers of the RapidMiner software, this book provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The new edition will update all chapters to RapidMiner 7, and will add at least six new chapters, including new chapters on text mining, time series, and educational data mining.

Open Source Data Warehousing And Business Intelligence

Author : Lakshman Bulusu
ISBN : 9781466578760
Genre : Computers
File Size : 47. 42 MB
Format : PDF
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Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW &

Open Source Business Intelligence

Author : Nils Clausen
ISBN : 9783839145760
Genre : Open source software
File Size : 52. 81 MB
Format : PDF, Mobi
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This book presents an in-depth introduction to the characteristics and capabilities of two data-mining and business intelligence software packages: RapidMiner and the Jaspersoft Business Intelligence (BI) Suite.

Rapidminer Studio Manual

Author : RapidMiner Team
ISBN : 1519554400
Genre :
File Size : 20. 10 MB
Format : PDF, ePub
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User Manual for RapidMiner 6.5

Fraud Detection With Data Mining

Author :
ISBN : OCLC:915452117
Genre :
File Size : 81. 22 MB
Format : PDF, ePub, Mobi
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Data Science

Author : Vijay Kotu
ISBN : 9780128147627
Genre : Computers
File Size : 45. 29 MB
Format : PDF, ePub, Mobi
Download : 531
Read : 268

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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

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