The Loss Function is a critical tool in the training process of machine learning models, used to evaluate the accuracy
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The Ultimate Guide to Loss Function: Essential Concepts, Formulas, and Their Impact on AI Model Performance
In our previous post, we explored the characteristics that define a good algorithm. Now, let’s delve into one of the
Continue readingMixed Data Learning: Leveraging Various Data Types in Machine Learning
When building a machine learning model, the types of data used can vary widely. One approach to handling this variety
Continue reading[Python] Jupyter Notebook and Jupyter Lab Shortcuts Guide
Jupyter Notebook and Jupyter Lab are essential tools for data scientists and developers. Using shortcuts in these environments can significantly
Continue readingPitfalls of Statistics – Simpson’s Paradox
The Subtleties of Statistics Statistics uniquely deal with uncertainty and randomness, distinguishing it sharply from other mathematical topics that are
Continue readingConvex Hull: 인공지능에 기하학 적용하기
Convex Hull(컨벡스 헐)은 계산 기하학의 기본 개념으로서 인공지능, 컴퓨터 그래픽스, 로보틱스 등 여러 분야에서 중요한 역할을 하고 있다. 이 포스트에서는Convex
Continue readingParticle Filters: Solving Non-Linear and Non-Gaussian Estimation Problems
Particle Filters are a powerful Sequential Monte Carlo method used to address non-linear and non-Gaussian estimation challenges. This approach has
Continue readingNon-Linearity and Non-Gaussian Estimation Problems
Non-linearity and non-Gaussian estimation problems are among the most challenging types of issues encountered in system modeling and data analysis.
Continue reading파티클 필터(Particle Filter)란 무엇인가?: 비선형, 비가우시안 문제 해결 방법
파티클 필터(Particle Filter)는 비선형 및 비가우시안 추정 문제를 해결하는데 사용되는 강력한 시퀀스 몬테카를로 방법(Sequential Monte Carlo method)으로, 이 방법은 로봇
Continue reading비선형(Non-Linearity) 및 비가우시안 (Non-Gaussian) 추정 문제
비선형 및 비가우시안 추정 문제는 시스템 모델링과 데이터 분석에서 흔히 마주치는 어려운 문제 유형이다. 이들 문제를 이해하기 위해서는 먼저 ‘비선형성(Non-Linearity)‘과
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