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WEKA - Data Mining with Open Source Machine Learning Tool

WEKA tool for data preparation, classification, regression, clustering, association rules mining, and visualization

Course Description

Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization.

Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this.

Weka is open source software issued under the GNU General Public License.

We have put together several free online courses that teach machine learning and data mining using R Programming, Python Programming, Weka Toolkit and SQL.

Yes, it is possible to apply Weka to process big data and perform deep learning!

Who this course is for:

  • Graduates or Pursuing BTech Students

Goals

  • Students can learn WEKA tool for data pre-processing, classification, regression, clustering, association rules, and visualization

Prerequisites

  • Basic Mathematics is enough
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Curriculum

  • File Resources
  • Waikato Environment for Knowledge Analysis (WEKA)
    44:25
  • Analysis & Prediction using WEKA Machine Learning Toolkit
    44:43
  • Python Libraries for Data Science
    22:32
  • Introduction to Data Science
    53:16
  • Introduction to Machine Learning
    44:38
Feedbacks
4.5
Course Rating
74%
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    Feedbacks (46)

  • Sidharth Kochu
    Sidharth Kochu

    excellent

  • Syed Kashif
    Syed Kashif

  • Suhail Haider
    Suhail Haider

  • Sudhir Mehta
    Sudhir Mehta

  • Gadisa Adamu Mitiku
    Gadisa Adamu Mitiku

  • M V S S Sastry (MANTHA V S S SASTRY)
    M V S S Sastry (MANTHA V S S SASTRY)

    Knowledgeble to me

  • Appasami G
    Appasami G

  • Baris Güngör
    Baris Güngör

  • Manthan Dalvi
    Manthan Dalvi

    Nive

  • DHYANI KUMAR KAMATI
    DHYANI KUMAR KAMATI

WEKA - Data Mining with Open Source Machine Learning Tool
This Course Includes
  • 3 hours
  • 7 Lectures
  • 6 Resources
  • Completion Certificate Sample Certificate
  • Lifetime Access Yes
  • Language English

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