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Machine Learning and Data Mining with Weka – For Beginners

March 15, 2022
2 Min Read
Machine Learning and Data Mining with Weka - For Beginners
Machine Learning and Data Mining with Weka - For Beginners

Machine Learning and Data Mining with Weka – For Beginners

Using Weka, you can start your journey into Machine Learning. You’ll learn how to build Predicative Machine Learning models.

What you’ll learn

Machine Learning and Data Mining with Weka – For Beginners

  • Download and set up the app. Weka.
  • Machine Learning can be used in real life.
  • Data sources and file types.
  • Classifies, filters and creates datasets.
  • Data mining can be used in real life.
  • Experimenting with and comparing Algorithms.

Requirements

  • A computer and a way to get to the internet.

Description

During this course, you will learn how to use Weka, a powerful open-source machine learning software that was developed in New Zealand by the University of Waikato. You will be able to use this software to learn about machine learning.

You will learn complex algorithm behaviors in a simple and clear way. By taking advantage of Weka’s advanced tools to run machine learning experiments, we can learn about algorithms, classifiers, and other functions like these ( Naive Bayes, Neural Network, J48, OneR, ZeroR, KNN, linear regression & SMO).

Hands-on:

  • An image, text, and document classification system, and a way to show data.
  • How to merge a lot of text and HTML files into one ARFF file with one command line.
  • There are two types of machine learning: supervised and unsupervised.

In Weka, the Graphical User Interface is very easy to use. It will take you from zero to hero. This is the way you will learn: You will compare different algorithms and check how well the machine learning algorithm works until you build your next predictive machine learning model.

Who this course is for:

  • A person interested in machine learning who doesn’t know how to write code.
  • Everyone who wants to learn more about data engineering and data science.

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