A Quick Guide to Data Mining using RapidMiner and Weka
A Quick Guide to Data Mining using RapidMiner and Weka
About the Book
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
About the Author
Table of Contents
- 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
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