
The Complete Guide to AB Testing
거친코딩
As the popularity and interest in AB Testing explodes, we will introduce Korea's first AB Testing lecture right now!
Basic
AB test, Statistics
For those who are new to machine learning, we will provide a clear understanding of the direction of study and basic concepts.
5,617 learners
Level Basic
Course period Unlimited

Reviews from Early Learners
5.0
Sona Lim
I no longer have any resistance to Google Colab, and I like that the lecture notes are posted on the blog so I can review them easily!
5.0
동해물과백두산이마르고닳도록
It's a great lecture.
5.0
현주
I was so satisfied with the mentoring with Mr. Geoun Coding that I decided to take this course as well. As expected, his teaching skills are great, and the class content is very informative! Thank you~! Please upload more lectures!!
Data preprocessing and processing using the Pandas library
Data visualization with Matplotlib and Seaborn libraries
Machine learning theory and practice using the scikit-learn library
Practical training using Kaggle data
With “rough but useful” rough coding,
Building Python Machine Learning from the Ground Up 📖
What you must know to start machine learning
Basic libraries and
Learn about real-world machine learning models!
#Pandas #Matplotlib #Seaborn
Machine learning is popular these days
I know it's good, but
I'm so lost as to where to start .
I have already learned machine learning
It is being applied, but
I'm not sure if I know this correctly .
Machine learning is becoming increasingly important!
Machine learning is the process of programming computers to learn from data using various statistical algorithms.
By the way, do you know why we use machine learning?
For example, let's take the case of creating a filter to handle spam within a service using traditional techniques.
In this case, we would create a spam filter like this:
The above approach may seem simple, but as the problem becomes more complex and the number of rules increases, maintenance becomes difficult.
On the other hand, machine learning can significantly improve maintainability and accuracy by automatically learning patterns that occur in spam.
As machine learning technology becomes widely known and receives much love and popularity, there are countless related courses available. However, most of these courses follow a similar pattern, focusing only on the topic or concept in a rigid manner. They lack explanations of how it can be applied and utilized in practice.
So, unlike other lectures, this lecture doesn't go straight into the topic of machine learning.
Instead, we will learn about the libraries that are absolutely necessary before actually doing machine learning, while freely preprocessing and visualizing real data , and then learn about the overall machine learning concepts.
💡 You can set the direction to start machine learning.
💡 You can learn the basic concepts of machine learning.
💡 You can develop the capabilities needed for analysis in addition to machine learning.
Based on the know-how we've accumulated over the years, we'll help you learn machine learning effectively.
Would you like to try machine learning together?
In Python data analysis
Anyone interested
Studying machine learning
For beginners
Data preprocessing and processing
Those who want to learn
Machine learning theory
Those who want to review
Please check your player knowledge!
Kaggle
Pandas
Matplotlib
Scikit-Learn
Just the essentials!
Many other products on the market
Unlike machine learning lectures,
Only the essential content
Let me give you a brief introduction.
Level up through practice
It doesn't stop at theory
scikit-learn built-in and
Using Kaggle data
We provide practical training.
Machine Learning for Beginners
Knowing the basics of Python
Tailored to beginners' level
Not difficult
You can learn the concept.
Data analysis too?
Not only machine learning concepts
Required for data analysis
Using the library
We will also introduce it.
✅ I will teach you effective study methods based on the know-how I have acquired through learning machine learning so far.
✅ We'll help you recall confusing concepts through theoretical lectures on overall machine learning models.
✅ If you have any questions while studying, please feel free to leave them. I'll try to answer them.
Please note before taking the class!
Check out the VLOG of knowledge sharer Rough Coding now! 🐯
Who is this course right for?
People interested in machine learning
Machine Learning Beginner
Anyone who wants to learn Python visualization
People who want to learn data preprocessing and processing
Need to know before starting?
Python
6,993
Learners
110
Reviews
102
Answers
4.8
Rating
3
Courses
Hello. I am "Rough Coding," a rough but truly informative data analyst.
Korea University, Department of Statistics (Graduated)
Korea University Graduate School, Department of Big Data Convergence (Enrolled)
QS World University Rankings Evaluation Committee Member
Completed the Advanced Artificial Intelligence course at Korea University, a SW-centered university
Session Leader of KUCC (Computer Club), Korea University
5-time Department Valedictorian and 1-time Overall Valedictorian at Korea University
Big Data Analysis Engineer Certification
Advanced Data Analytics Semi-Professional (ADsP) Certification
I am currently working at "one of the NAVER/Kakao companies" performing data collection, processing, analysis, prediction, visualization, and task automation using Python and visualization tools (Tableau).
Efficient study methods for students dreaming of a career in data analysis
Mentoring for junior analysts currently working in the field of data analysis
Those who are not in an IT role but wish to apply IT technology to their own work.
Conducted remotely via Zoom
Requirements: Computer, camera, earphones
Mentoring will proceed based on pre-prepared questions or your current situation.
The beginning is the most important part of everything. Let's make sure to achieve what you want with burning passion!
rough_coding@naver.com
All
25 lectures ∙ (9hr 0min)
All
48 reviews
4.9
48 reviews
Reviews 2
∙
Average Rating 5.0
5
I no longer have any resistance to Google Colab, and I like that the lecture notes are posted on the blog so I can review them easily!
I'm even happier that you're satisfied~!! As you said, all the lecture contents and source code for the lecture are all on the blog, so if you get stuck while studying, please refer to the blog. Thank you! I will always cheer you on as you study hard. Thank you. -Rough Coding Dream-
Reviews 3
∙
Average Rating 5.0
5
I was so satisfied with the mentoring with Mr. Geoun Coding that I decided to take this course as well. As expected, his teaching skills are great, and the class content is very informative! Thank you~! Please upload more lectures!!
Ah! You also took a lecture after the mentoring! I will come back at the end of October for a lecture on personalized recommendation systems :) -Rough Coding Dream-
Instructor This is a question about pension data Practice data url: https://drive.google.com/drive/folders/149jcCyJFKKG5MFaPNWnYYqM2EkzgRz2P?usp=sharing Create a new data folder (machine_learning_data) and upload files If you go to the above location, you will see a shared folder called "machine_learning_data", but there are only jpg files and cvs files in it, and I could not find any files related to the lecture. If I am looking for the wrong location, please let me know.
Reviews 5
∙
Average Rating 5.0
5
I love it so much
Thank you :) I will come back with a better lecture. -Rough Coding Dream-
Reviews 1
∙
Average Rating 5.0
5
It was great that I could apply the basic grammar of Python to modeling and even case studies right in Kaggle! I can't believe this level of quality is available for free lectures.. I'm looking forward to the series of lectures :)
I'm glad that it was helpful! I'll come back with a better lecture -Rough Coding Dream-
Free
Check out other courses by the instructor!
Explore other courses in the same field!