Machine Learning with Java and Weka
What you'll learn
- Create a data product using Weka and Java
- Computer Skills, Java Programming
Why learn Data Analysis and Data Science?
According to SAS, the five reasons are
1. Gain problem solving skills
The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life.
2. High demand
Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase.
3. Analytics is everywhere
Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.
4. It's only becoming more important
With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities.
5. A range of related skills
The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths. Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.
The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities.
This is the bite-size course to learn Java Programming for Machine Learning and Statistical Learning with the 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, and linear regression, and evaluate your models very soon after learning the course.
Getting Started 2
Getting Started 3
Data Mining Process
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 in Weka and Java
Agglomeration Clustering in Weka and Java
Decision Tree ID3 Algorithm
Decision Tree in Weka and Java
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 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
SVBook Pte. Ltd. started in April 2016. SVBook Pte. Ltd. offers affordable, easy to read Data Mining, Text Mining, Data Analytics, Programming books for professional and lifelong learning. SVBook Pte. Ltd. offers courses at EMHAcademy. SVBook Pte. Ltd. developed softwares over the time, and uploaded them at DSTK_Tech. SVBook Pte. Ltd. courses, books and softwares assists people to step into new fields of Data Science, Internet of Things, Smart Cities and etc. before going into more advanced courses at Coursera and EdX, which are at University Level.