✍ To improve business results through a recommendation system,

This has already been proven by many IT/commerce/platform companies.

추천 알고리즘 이해부터 다양한 서비스에 따른 추천시스템 구현 방법까지

▶ From understanding recommendation algorithms to how to implement recommendation systems based on various services

A service where the recommendation system is the core, Food Delivery's Yogiyo Machine Learning Engineer will fully help you get started with the recommendation system.

Is it enough to learn algorithms and theory?

Service-optimized problem solving

This is the beginning of the recommendation system.

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In e-commerce and food delivery, I've experienced both areas where 'recommendations' play an important role in service. While working as a recommendation system engineer, I also developed recommendation algorithms suitable for each situation (context) that occurs in the service, and also developed a recommendation system based on personalization (personalization). (E-commerce service personalization/Delivery app service recommendation upgrade)

What I felt while building a recommendation system in the business It is more important to go beyond algorithms and theories to solve problems according to each business situationIt was.

Trying one line of a package

It's not a recommendation system.

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When I search for materials to study recommendation systems, I often finish by running a line of package code after explaining a paper or theory of an algorithm in a verbose manner. However, simply knowing the theory and running a package line by line is not a recommendation system.

추천이 중요한 역할을 하는 두 서비스, 이커머스와 푸드 딜리버리를 모두 경험해본 현직자에게 배워보세요

▶ Learn from an incumbent who has experienced both e-commerce and food delivery, where recommendations play an important role

To accurately understand the “situation” and “service” elements of “recommendation,” and to find solutions that match themThis is the process of properly establishing a recommendation system. Algorithms and theories can also be fully learned through papers, Business problem solving is an area that you can't understand at all unless you listen to business people.

Classes are held with recommended system engineers who have experienced both e-commerce and food delivery services so that they can take a practical perspective as it is. Starting with understanding algorithms, we will create a recommendation system tailored to the service and each business situation.

클래스 커리큘럼

▶ Class curriculum

📌 Why was this algorithm used in this situation

📌 How can business problems be improved

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In this class, students study recommendation systems with a focus on theory (30%) + practical code solving (70%). But it's not all theory or code. Rather, we'll focus on why these algorithms are used in this situation and how the problem can be improved.

Through this class, I will tell you all about what a recommendation system is, and how to define and solve the 'situation' and 'service' elements that I have learned through my experience with user services.

수강 대상

▶ Course Eligibility

강의 특징

▶ Course features

Introduction to recommendation systems from a machine learning engineer in Yogiyo

Introduction to recommendation systems from a machine learning engineer in Yogiyo