Getting Started with
Machine Learning
Jim Liang | Sep, 2019 Ver. 0.96
Created by: Jim Liang
:: Table of contents
Image Designed by Asierromero / Freepik/
Part 1: The fundamental concept
• Overview ⇲
• Business Understanding ⇲
• Data Understanding ⇲
• Data Preparation ⇲
• Modelling ⇲
• Model Evaluation ⇲
• Model Deployment ⇲
• Miscellaneous Topics ⇲
Last updated on Sep, 2019. 禁止用于盈利性目的
Part 3: Other topics ⇲
• Large scale machine learning ⇲
• What to do when there is no enough
data ? ⇲
Part 2: Well-known algorithms ⇲
• Nearest Neighbor ⇲
• Support Vector Machines ⇲
• Linear Regression ⇲
• Logistic Regression ⇲
• Neural Network -1 ⇲
• Gradient Descent ⇲
• Neural Network - 2 ⇲
• Convolutional Neural Networks -1 ⇲
• Convolutional Neural Networks - 2 ⇲
• Naïve Bayes ⇲
• K-means ⇲
• Decision Trees ⇲
• AdaBoost ⇲
• Random Forest ⇲
• PCA ⇲
The fundamentals
of machine learning
Part 1
