Getting Started with Machine Learning Jim Liang 1 Sep 2019 Ver. 0.96
:Kind Reminder Pleaseread thisdocinfullscreenmode Howtoquicklynavigatewithinthisdocument? Acrobat Reader FileEdit MAA window Help Rotate View P Nearest Neighbor Home Tools Getting St Page Navigation Support Vector Machines Click on this icon b Page Display H Q Zoom A 0 Linear Regressior Tools > Logistic Regression Show/Hide P Neural Network Display Theme Gradient Descent Table of contents Read Mode. Full Screen Mode XH XL K sefeg eON Tracker... K-means Read Out Loud PCA Decision Trees 原始文档是powerpoint制作并转成PDF文件 AdaBoost 所以为了更好地阅读，请切换到全屏模式 Random Forest
:Table of contents Part 1: The fundamental concept Part 2:Well-known algorithms Part 3: Other topics Overview Nearest Neighbor Large scale machine learning ≥ Business Understanding ≥ Support Vector Machines What to do when there is no enough Data Understanding Linear Regression data ? Data Preparation Logistic Regression Modelling Neural Network -1 Model Evaluation Gradient Descent Model Deployment ≥ Neural Network - 2 Miscellaneous Topics Convolutional Neural Networks -1 ≥ Convolutional Neural Networks - 2 Naive Bayes K-means Decision Trees AdaBoost Random Forest .PCA Last updlated on Sep 2019.聚止用于盈利性目的
The fundamentals Part 1 of machine learning
01 overview Table of contents
MLN 机器学习学习笔记(英文版).pdf
