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Compared to other courses, it is structured at a level that is easy for beginners to understand.

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This lecture is the second lecture of the data science course developed by TEAMLAB and Inflearn, Introduction to Machine Learning from Scratch. Introduction to Machine Learning from Scratch consists of Part I and Part II.

This lecture was produced with the support of WADIZ funding prepared by TEAMLAB and Inflearn.

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Introduction to Machine Learning from Scratch

본 강의는 TEAMLAB과 Inflearn이 함께 구축한 데이터 사이언스 과정의 두 번째 강의인 밑바닥 부터 시작하는 머신러닝 입문 입니다. 밑바닥부터 시작하는 머신러닝 입문은 Part I과 Part II로 구성되어 있습니다.

본 강의는 TEAMLAB과 Inflearn이 함께 준비한 WADIZ 펀딩의 지원을 받아제작되었습니다.

TeamLab

입문

초급

중급이상

Machine Learning(ML)

머신러닝

밑바닥 부터 시작하는 머신러닝 입문

Chapter 1 - Introduction to Machine Learning

Chapter 2 - Warm Up Section: An understanding of data

&#039;  Supplements - Linear algebra

Chapter 3 - Numpy Section

Chapter 4 - Pandas Section #1

Chapter 5 - Pandas Section #2

Chapter 6 - Matplotlib Section & Miniproject

Chapter 7 - Linear Regression

Chapter 8 - Linear Regression extended

Chapter 9 - Logistics Regression

Chapter 10 - Logistics Regression extended

Chapter 11 - Naive Bayesian Classifier

&#039; Supplements : Text handling Lab: News categorization

Chapter 12 - Decision Tree

Chapter 13 - Ensemble

Chapter 14 - Performance tuning