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機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

Курс от National Taiwan University

Средний≈ 9.3 чКитайский (Тайвань)

О курсе

Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. Our two sister courses teach the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. This second course of the two would focus more on algorithmic tools, and the other course would focus more on mathematical tools. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。我們的兩項姊妹課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。本課程將較為著重方法類的工具，而另一課程將較為著重數學類的工具。]

Навыки, которые вы освоите

Machine Learning Algorithms Regression Analysis Machine Learning Logistic Regression Supervised Learning Feature Engineering Model Evaluation Model Training Verification And Validation Statistical Methods Algorithms Applied Machine Learning Classification Algorithms Model Optimization Machine Learning Methods Data Transformation

Программа курса

8 модулей · 38 учебных материалов

01 第九講：Linear Regression8 материалов

Linear Regression

NTU MOOC 課程問題詢問與回報機制Чтение Linear Regression ProblemВидео Linear Regression AlgorithmВидео Generalization IssueВидео

Учитесь у экспертов

林軒田

教授 (Professor)

機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

О курсе

Навыки, которые вы освоите

Программа курса

Linear Regression

Учитесь у экспертов

林軒田

Course Information

Logistic Regression

Linear Models for Classification

Nonlinear Transformation

Hazard of Overfitting

Regularization

Validation

Three Learning Principles