Machine Learning and Data Mining with Weka – For Beginners

Learn how to start your Machine Learning journey with Weka to Build your next Predicative Machine Learning Models.

This introductory course will help make your machine learning journey easy and pleasant , you will be learning by using the powerful Weka open source machine learning software, developed in New Zealand by the University of Waikato.

What you’ll learn

  • Download and Install Weka.
  • Practical use of Machine Learning.
  • Data sources and file formats.
  • Preprocess, Classifies, Filters & Datasets.
  • Practical use of Data Mining.
  • Experimenting & Comparing Algorithms.

Course Content

  • Introduction –> 8 lectures • 20min.
  • Practical use of Data Mining with Weka –> 4 lectures • 14min.
  • Practical use of Machine Learning with Weka –> 3 lectures • 6min.
  • Experiment#1: OneR vs ZeroR classifiers –> 4 lectures • 8min.
  • Experiment#2: J48 classifier performance –> 2 lectures • 3min.
  • How to build & configure J48 classifier? –> 3 lectures • 7min.
  • Experiment#3: KNN Regression Algorithm –> 2 lectures • 5min.
  • Experiment#4: Linear Regression Algorithm –> 3 lectures • 6min.
  • Data Visualization with Weka –> 2 lectures • 7min.
  • Experiment#5: Image classification –> 5 lectures • 7min.
  • Document Classification with Weka –> 3 lectures • 4min.
  • Text Classification with Weka –> 5 lectures • 17min.
  • Challenge & Practical Tests –> 2 lectures • 3min.
  • The Bonus –> 8 lectures • 24min.

Machine Learning and Data Mining with Weka - For Beginners

Requirements

  • A computer and internet connection..

This introductory course will help make your machine learning journey easy and pleasant , you will be learning by using the powerful Weka open source machine learning software, developed in New Zealand by the University of Waikato.

You will learn complex algorithm behaviors in a straightforward and uncomplicated manner. By exploiting Weka’s advanced facilities to conduct machine learning experiments, in order to understand algorithms, classifiers and functions such as ( Naive Bayes, Neural Network, J48, OneR, ZeroR, KNN, linear regression & SMO).

Hands-on:

  • Image, text & document classification & Data Visualization
  • How to convert bulk text&HTML files into a single ARFF file using one single command line
  • Difference between Supervised & Unsupervised Machine Learning methods
  • Practical tests, quizzes and challenges to reinforce understanding

Weka’s intuitive, the Graphical User Interface will take you from zero to hero. You will be learning by comparing different algorithms, checking how well the machine learning algorithm performs till you build your next predicative machine learning model.

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