$19.99
per month
Video
Feb 2018
2hrs 53mins
1st Edition
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• Start by building your basic knowledge of statistics, then move on to some classical data mining algorithms such as K-means and Apriori
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• Apply statistical and data mining techniques to analyze and interpret results using CHAID, Linear Regression, and Neural Networks
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• Acquire a wider repertoire of analytical skills to help you make smart decisions for both customers and industries
Data Science is an ever-evolving field. Data Science includes techniques and theories extracted from statistics, computer science, and machine learning. This video course will be your companion and ensure that you master various data mining and statistical techniques.
The course starts by comparing and contrasting statistics and data mining and then provides an overview of the various types of projects data scientists usually encounter. You will then learn predictive/classification modeling, which is the most common type of data analysis project. As you move forward on this journey, you will be introduced to the three methods (statistical, decision tree, and machine learning) with which you can perform predictive modeling. Finally, you will explore segmentation modeling to learn the art of cluster analysis. Towards the end of the course, you will work with association modeling, which will allow you to perform market basket analysis.
This course uses SPSS v25, while not the latest version available, it provides relevant and informative content for legacy users of SPSS.
All the resource files are added to the GitHub repository at: https://github.com/PacktPublishing/Advanced-Statistics-and-Data-Mining-for-Data-Science
This course is suitable for developers who want to analyze data, and learn data mining, and statistical techniques in depth. This is an ideal course for those in Data Analytics, Data Management, Business Analytics, Business Intelligence, Information Security, Information Center, Finance, Marketing, and Data Mining; and specifically data developers, data warehousers, data consultants, and statisticians—across all industries and sectors
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• Get familiar with advanced statistics and data mining techniques
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• Differentiate between the various types of predictive models
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• Master linear regression
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• Explore the results of a decision tree
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• Work with neural networks
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• Understand when to perform cluster analysis and when to use association modeling