Machine Learning with Java and Weka

What you'll learn

Create a data product using Weka and Java

Requirements

Computer Skills, Java Programming

Description

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.


Content

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

Who this course is for:

Beginner Data Analyst or Data Scientist interested in using Weka in Java