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The Post Java Machine Learning Weka Intermediate for 7 hours

  The Post Java Machine Learning Weka Intermediate for 7 hours

Udemy Coupon ED | The Post Java Machine Learning Weka Intermediate for 7 hours

2nd class for everyone who want to widespread java machine learning. Introduce Weka, which can both design and program Java machine learning. 2. What (Lectures). Here's a real machine learning application Get Course
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What you'll learn
  • Practical Application of Java Machine Learning Using Weka
  • Adopting an Optimal Algorithm by Comparative Analysis
  • Drawing up the basis for decision making using feature (attribute) selection only
  • Formal text mining such as surveys
  • Proof of relationship by classification analysis after association analysis
  • Application of Artificial Neural Network for Image Analysis
  • Weka and R Program Interlink
 Description

1.Why (purpose)
  The goal is to quickly establish a decision cooperative system with data.:
  Introduce Weka, which can both design and program Java machine learning.

2. What (Lectures)
  Here's a real machine learning application with weka alone
   : we've adapted a variety of application cases into familiar content.
  Then shall we briefly introduce the contents?

2.1 Adopting an Optimal Algorithm by the Experimenter
  : Adopting an Optimal Model through a P-value Statistical Test (where did you hear that?)

2.2 Making decisions with the feature selection
: creating decision information with a specific (attribute) selection. R program linkage is a bonus.

2.3 Survey Text Mining
  :  No more wrestling with the difficult Hangul Formosa! A simple Korean survey can be done with basic functions.

2.4 Correlation and Classification of U.S. House Elections in 84
  :  The Obama camp did not anticipate election pledges, but chose statistical analysis of its website to raise campaign funds: What's really important is to know which pledges are directly linked to election?

2.5 Image Analysis by Artificial Neural Network and Image Filter
  : Tired of waiting for a beta version of dl4j: Introducing Weka's built-in Artificial Neural Network and wekadeepleasing4j.

2.6 Estimate when a course is completed through regression analysis
  : Used to determine how long a lecture should be postponed.

3. Method
The above process is explained in three order as follows.

3.1 Theoretical Description
  : Background knowledge is brief. It's really simple, it's all about the point.

3.2 KnowledgeFlow Design
  : Weka's Best Advantage - Machine learning is possible without programming.

3.3 Java programming
  : Another advantage of weka, weka provides everything for design and coding.

4. IF (effectiveness)
  You can apply loaded data analysis to traditional IT systems that consist of Java platforms
  : Would you like to know how to take a post way in traditional IT so that you can analyze it well on ICBMs?

You get a way to understand the real world with your data
  : to understand the unseen reality with your data.

5. Beginner's reflection point → Supplementary intermediate course
  It's an intermediate course that has improved more than a beginner's class for the base change of Java machine learning.:
  Through feedback and self-reflection from the students on the beginner's course, we have improved more than the beginner's course.

6. Lecture environment
  Use weka 3.9.3 for Windows OS
  (3.9.4 has a bug when importing ANSI type files).

7. Lecture materials
  : You can download it by clicking the cloud icon in the second class in section 1
     (installing Weka software and downloading course materials). (55 MB)

8. Continuation of Extra lecture
  I  will continue to upload lecture from the students' good questions and useful information from other media.
  I look forward to strengthening communication with my students and improving their satisfaction with lectures.
  Exclude hard, requirements, or personal questions.

9. Caution
You can see Korean in the video or lecture materials.
But you don't have to worry that you don't understand Korean.
The Korean language you see in the lecture can be considered to only non-utf-8 data.

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