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Java Machine Learning Weka Beginner

There is no need to ignore or fear machine learning. Machine learning is easy, but let's think about where to apply machine learning. The direction of machine learning expansion in Java is expected to be similar to the current Python, R strength, and future coexistence of Python, R, and Java, like iOs. The purpose of this lecture is to build a DIKW collaboration system between domain experts and IT professionals.

(4.9) 20 reviews

1,993 learners

  • javaraml
Java
Machine Learning(ML)
Weka
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Reviews from Early Learners

What you will learn!

  • Building a collaborative system between domain experts who know machine learning and Java developers who know coding

  • Machine learning without coding

  • Java Machine Learning S/W Weka (Beginner)

  • Machine Learning Java Implementation

What is your choice in the situation below?

1) Let's learn machine learning.

Don't be afraid or ignore it. It's that easy.

It's difficult to know where and how to apply machine learning.

2) Expanding machine learning in Java

Currently, R and Python are strong, but compatibility with Java is expected in the future.

3) Pretend to know coding even if you don't, and pretend to know more if you do

Machine learning is possible with just the free Weka UI built in Java.

Knowing how to code allows you to systematize (share, regularize) machine learning.

Note

You can download all lecture video materials from the link below.

Blog: https://bulleten.blog.me/221669663531

gitHub: https://github.com/javaramachinelearning/WekaForKorean_BASE

- knowledgeflow save file,

- Java source code,

- jar file for eclipse

- Lecture materials pdf

The content for each lecture is organized in the blog linked below the video.

There are a total of 22 lectures, each lasting approximately 10 to 15 minutes.

We will respond to your questions promptly, but may not be able to respond until after 6:00 PM.

Recommended for
these people

Who is this course right for?

  • Domain expert who doesn't know how to code

  • Machine Learning Planner

  • Java developer with 1+ years of practical experience (eclipse +)

Need to know before starting?

  • Machine learning interest

  • Java coding (not required, but it's better to know)

  • ADsP (Data Analysis Associate Professional) holder (not required, but can understand quickly)

Hello
This is

2,098

Learners

29

Reviews

15

Answers

4.9

Rating

3

Courses

정보화 기획/구축/진단 업무를 수행하였고 스몰데이터분석을 실무에 적용하고 있습니다.
현재 데이터분석 분야는 코딩이 과대포장된 진입장벽을 만들었다는 것을 알게 되었습니다.
이제는 거품을 걷어내고 데이터분석의 저변화와 자바머신러닝을 준비하고
직접 강좌로 자바머신러닝을 확산할 동료들을 만나는 것이 저의 목적입니다.
더나아가 POST 정보화시대를 대비하고 영위하는 미래의 모습을 그려봅니다.

Curriculum

All

23 lectures ∙ (4hr 45min)

Published: 
Last updated: 

Reviews

All

20 reviews

4.9

20 reviews

  • goodday757306님의 프로필 이미지
    goodday757306

    Reviews 2

    Average Rating 5.0

    5

    91% enrolled

    I was wondering where Java Machine Learning was, and it was here. I enjoyed the lecture.

    • heejungyang3435님의 프로필 이미지
      heejungyang3435

      Reviews 20

      Average Rating 4.7

      4

      30% enrolled

      • leehm12239214님의 프로필 이미지
        leehm12239214

        Reviews 1

        Average Rating 4.0

        4

        13% enrolled

        • ismartkorea015777님의 프로필 이미지
          ismartkorea015777

          Reviews 1

          Average Rating 5.0

          5

          43% enrolled

          You can get machine learning support in Java!!

          • hee00750727님의 프로필 이미지
            hee00750727

            Reviews 2

            Average Rating 5.0

            5

            65% enrolled

            Thank you so much for your help

            Free

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