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Learn R : 12 Books (Free PDFs!) and Online Resources - YOU CANalytics

#artificialintelligence

This book is a high quality statistical text with R as the software of choice. If you want to be comfortable with fundamental concepts in parallel with learning R, then this is the book for you. Having said this, you will love this book even if you have studied advanced statistics. The book also covers some advanced machine learning concepts such as support machine learning (SVM) and regularization.


Useful R Packages that Aligns with The CRISP DM Methodology

@machinelearnbot

As we all know CRISP DM stands for Cross Industry Standard Process for Data Mining is a process model that outlines the most common approach to tackle data driven problems. Per the poll conducted by KDNuggets in 2014 this was and "is" one of the most popular and widest used methodology. This method of gleaning insights out of the data is very dear to the industry experts and data miners. As the title suggest I will align some of the most useful R packages with this most popular and simplistic data processing model and before getting into specific packages, there is one GUI based R Package named Rattle which is very much based around these steps. Rattle's tab based interface provides a step by step flow which is a replica of the CRISP DM method.


Useful R Packages that Aligns with The CRISP DM Methodology

@machinelearnbot

As we all know CRISP DM stands for Cross Industry Standard Process for Data Mining is a process model that outlines the most common approach to tackle data driven problems. Per the poll conducted by KDNuggets in 2014 this was and "is" one of the most popular and widest used methodology. This method of gleaning insights out of the data is very dear to the industry experts and data miners. As the title suggest I will align some of the most useful R packages with this most popular and simplistic data processing model and before getting into specific packages, there is one GUI based R Package named Rattle which is very much based around these steps. Rattle's tab based interface provides a step by step flow which is a replica of the CRISP DM method.


Data Mining with R: Go from Beginner to Advanced!

@machinelearnbot

This is a "hands-on" business analytics, or data analytics course teaching how to use the popular, no-cost R software to perform dozens of data mining tasks using real data and data mining cases. It teaches critical data analysis, data mining, and predictive analytics skills, including data exploration, data visualization, and data mining skills using one of the most popular business analytics software suites used in industry and government today. The course is structured as a series of dozens of demonstrations of how to perform classification and predictive data mining tasks, including building classification trees, building and training decision trees, using random forests, linear modeling, regression, generalized linear modeling, logistic regression, and many different cluster analysis techniques. The course also trains and instructs on "best practices" for using R software, teaching and demonstrating how to install R software and RStudio, the characteristics of the basic data types and structures in R, as well as how to input data into an R session from the keyboard, from user prompts, or by importing files stored on a computer's hard drive. All software, slides, data, and R scripts that are performed in the dozens of case-based demonstration video lessons are included in the course materials so students can "take them home" and apply them to their own unique data analysis and mining cases.


The Top 10 Data Mining Tools of 2018 Analytics Insight

#artificialintelligence

But it is not a cake walk to analyze it as greater things come at a greater cost. With the exponential growth in data, there requires a process to extract meaningful information as conclude to useful insights. Data mining is the process where the discovery of patterns among large sets of data to transform it into effective information is performed. This technique utilizes specific algorithms, statistical analysis, artificial intelligence and database systems to juice out the information from huge datasets and convert them into an understandable form. This article lists out 10 comprehensive data mining tools widely used in the big data industry.