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Data Science

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Data Analysis

Data science that I just tried with R

This is a lecture that teaches you how to do data science through R. You will learn line by line, from loading data to building models and model performance strategies.

(3.8) 6 reviews

77 learners

Level Intermediate

Course period Unlimited

  • coco
R
R
R
R

Reviews from Early Learners

Reviews from Early Learners

3.8

5.0

djchoi

100% enrolled

It's a useful lecture.

5.0

나경태

100% enrolled

Good, good

5.0

plsch

100% enrolled

I heard it well.

What you will gain after the course

  • How to fit a machine learning model with R

  • How to increase machine learning model performance

🙆🏻‍♀ This is a lecture that teaches you how to do data science using R.
Learn step-by-step, from data loading to model building and model performance strategies. 🙆🏻‍♂

"99.9% livecoding, learning DataScience line by line."

✅ Precautions

This course focuses more on practice than theory .
You should have basic knowledge of R and general knowledge of machine learning .

🗒 Course Introduction

You've learned R and machine learning, but don't know how to do data analysis?
This course teaches you everything from data entry to machine learning model building and strategies for improving model performance, all while typing code line by line.

🌈 Just try fitting a machine learning model

  • Let's fit linear regression and decision tree using basic data in R.
  • We'll talk about how to interpret regression models and split training and validation data.

🌈 Building a Heart Disease Prediction Model (Linear Regression)

  • Let's build a heart disease prediction model using logistic regression analysis.
  • Learn about variable selection methods and fit stepwise/forward/backward regression, respectively.

🌈 Machine Learning with Movie Review Sentiment Analysis

  • We do everything from collecting movie review data to building emotional models.
  • Let's build a model using the Decoument Term Matrix, the most basic text preprocessing method.
  • Let's apply the ensemble learning technique.
  • We will vectorize reviews using Word2vec and fit a machine learning model to them.

🌈 Learn machine learning through Kaggle data analysis

  • We talk about how classes deal with imbalanced data.
  • RandomOversampling/SMOTE/DBSMOTE, etc. are suitable.
  • Depending on the problem, we will think about ways to improve the model's performance and implement them ourselves.

🙋🏻‍♂️ I'm curious!

Q. How much R do I need to know?
A. You should be able to basically import and preprocess data. The introductory R programming course is mandatory, and the intermediate course is optional.

Q. How much knowledge of machine learning and statistics do I need?
A. You should have basic knowledge of statistics (t.test/anova, etc., at the undergraduate liberal arts level) and theoretical knowledge of machine learning (at the undergraduate major level) to make the course easier to follow.

Recommended for
these people

Who is this course right for?

  • I have studied statistics and machine learning, but I have no practical experience.

  • Anyone who wants to fit multiple machine learning models

Need to know before starting?

  • General knowledge of R

  • Statistics and Machine Learning Fundamentals

Hello
This is

8,388

Learners

509

Reviews

136

Answers

4.4

Rating

20

Courses

I am an unemployed scholar who majored in statistics as an undergraduate, earned a PhD in industrial engineering (artificial intelligence), and is still studying.

Awards ㆍ 6th Big Contest: Game User Churn Algorithm Development / NCSOFT Award (2018) ㆍ 5th Big Contest: Loan Delinquency Prediction Algorithm Development / Korea Association for ICT Promotion

Awards

ㆍ 6th Big Contest Game User Churn Prediction Algorithm Development / NCSOFT Award (2018)

ㆍ 5th Big Contest Loan Defaulter Prediction Algorithm Development / Korea Association for ICT Promotion (KAIT) Award (2017)

ㆍ 2016 Weather Big Data Contest / Korea Institute of Geoscience and Mineral Resources President's Award (2016)

ㆍ 4th Big Contest: Development of Insurance Fraud Prediction Algorithm / Finalist (2016)

ㆍ 3rd Big Contest Baseball Game Prediction Algorithm Development / Minister of Science, ICT and Future Planning Award (2015)

* blog : https://bluediary8.tistory.com

My primary research areas are data science, reinforcement learning, and deep learning.

I am currently doing crawling and text mining as a hobby :)

I developed an app called Marong that uses crawling to collect and display only popular community posts,

I also created a restaurant recommendation app by collecting lists of famous restaurants and blog posts from across the country :) (it failed miserably..)

I am currently a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting blog posts and lists of top-rated restaurants across the country :) (though it failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

Curriculum

All

32 lectures ∙ (7hr 23min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

6 reviews

3.8

6 reviews

  • doit9383님의 프로필 이미지
    doit9383

    Reviews 5

    Average Rating 4.2

    4

    100% enrolled

    This is a lecture that you can listen to if you have some basic knowledge of machine learning and R.

    • cdjcys35님의 프로필 이미지
      cdjcys35

      Reviews 18

      Average Rating 4.7

      5

      100% enrolled

      It's a useful lecture.

      • goodboyboxer2186님의 프로필 이미지
        goodboyboxer2186

        Reviews 3

        Average Rating 5.0

        5

        100% enrolled

        Good, good

        • plsch5171님의 프로필 이미지
          plsch5171

          Reviews 35

          Average Rating 4.9

          5

          100% enrolled

          I heard it well.

          • razyen5988님의 프로필 이미지
            razyen5988

            Reviews 1

            Average Rating 1.0

            1

            22% enrolled

            I've taken a lot of online lectures, but Colsera Fast Campus... was the worst. The lectures are too stream-of-consciousness, so it's messy and distracting. There are too many instances of code being changed because they're wrong. (I've taken 4 lectures so far, and it's like this..) I don't know much, so I'm just listening, but I keep writing and erasing, writing and erasing... It seems like the content really needs to be processed for lectures. I'm not suggesting that there's a problem with the instructor's skills, but I'm saying that lectures need to have a quality check. I'm evaluating it because it's really hard to listen to.

            $55.00

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