Machine Learning with Java and Weka

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

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This is the bite size course to learn Java Programming for Machine Learning and Statistical Learning with Weka library. In CRISP DM data mining process, machine learning is at the modeling and evaluation stage. 

You will need to know some Java programming, and you can learn Java programming from my "Create Your Calculator: Learn Java Programming Basics Fast" course. You will learn Java Programming for machine learning and you will be able to train your own prediction models with naive bayes, decision tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course.

Basic knowledge
  • Computer Knowledge
  • Basic coding knowledge

What will you learn


  • Introduction
  • Getting Started
  • Getting Started 2
  • Getting Started 3
  • Data Mining Process
  • Data set
  • Split Training and Testing dataset
  • CReate Java Application using Netbeans with Weka Jar
  • Simple Linear Regression
  • LInear Regression using Weka and Java
  • LInear Regression using Weka and Java 2
  • LInear Regression using Weka and Java 3
  • KMeans Clustering
  • KMeans Clustering in Weka and Java
  • Agglomeration Clustering
  • Agglomeration Clustering in Weka and Java
  • Decision Tree ID3 ALgorithm
  • Decision Tree in Weka and Java
  • KNN Classification
  • KNN in Weka and Java
  • Naive Bayes Classification
  • Naive Bayes in Weka and Java
  • Neural Network Classification
  • Neural Network in Weka and Java
  • What Algorithm to Use?
  • Model Evaluation
  • Model Evaluation in Weka and Java
  • CReate a Data Mining Software
  • CReate a Data Mining Software 2
Course Curriculum
Number of Lectures: 29 Total Duration: 02:20:59

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