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You will develop the ability to define problems based on data and clearly explain the rationale and decision-making process behind them. Additionally, rather than focusing solely on the performance of a single model, you will acquire a pipeline-oriented mindset that evaluates the completeness and reliability of the entire machine learning workflow. Furthermore, you will strengthen your problem-solving skills by tracing back the causes of errors when they occur and deriving improvement directions, and through end-to-end project experience, you will acquire practical ML pipeline capabilities that can be immediately applied in real-world settings.

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Machine Learning Pipeline

ai 코딩

AI 코딩

backend basics

백엔드이해하기

실습 중심

입문

초급

중급이상

Machine Learning(ML)

파이썬

Python

도커

Docker

텐서플로

Tensorflow

Pipeline Overview

Data Preparation

Model Development

Evaluation & Practice (t-Test)