In this course you will learn about #advanced #data #mining which will boost your data mining skill to the utmost level.
** Topics of this course **
Advanced Data Mining (1.1: Introduction)
Advanced Data Mining (1.2: Linear regression with lags)
Advanced Data Mining (1.3: timeseriesForecasting package)
Advanced Data Mining (1.4: Looking at forecasts)
Advanced Data Mining (1.5: Lag creation, and overlay data)
Advanced Data Mining (1.6: Application: Infrared data from soil samples)
Advanced Data Mining (2.1: Incremental classifiers in Weka)
Advanced Data Mining (2.2: Weka’s MOA package)
Advanced Data Mining (2.3: The MOA interface)
Advanced Data Mining (2.4: MOA classifiers and streams)
Advanced Data Mining (2.5: Classifying tweets)
Advanced Data Mining (2.6: Application to Bioinformatics – Signal peptide prediction)
Advanced Data Mining (3.1: LibSVM and LibLINEAR)
Advanced Data Mining (3.2: Setting up R with Weka)
Advanced Data Mining (3.3: Using R to plot data)
Advanced Data Mining (3.4: Using R to run a classifier)
Advanced Data Mining (3.5: Using R to preprocess data)
Advanced Data Mining (3.6: Application: Functional MRI Neuroimaging data)
Advanced Data Mining (4.1: What is distributed Weka?)
Advanced Data Mining (4.2: Installing with Apache Spark)
Advanced Data Mining (4.3: Using Naive Bayes and JRip)
Advanced Data Mining (4.4: Map tasks and Reduce tasks)
Advanced Data Mining (4.5: Miscellaneous capabilities)
Advanced Data Mining (4.6: Application: Image classification)
Advanced Data Mining (5.1: Invoking Python from Weka)
Advanced Data Mining (5.2: Building models)
Advanced Data Mining (5.3: Visualization)
Advanced Data Mining (5.4: Invoking Weka from Python)
Advanced Data Mining (5.5: A challenge, and some Groovy)
Advanced Data Mining (5.6: Course summary)
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Course: http://weka.waikato.ac.nz/
YouTube: / @wekamooc
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