Machine Learning

Note

A collection of Markdown files where I took note to understand the concept of machine learning.

• Imbalance binary classification
• Linear Discriminant Analysis (LDA)
• Logistic regression
• Cross-Validation
• Decision tree
• Boosting
• Bagging
• Support vector machine
• Clustering
• Linear model

Book

• An Introduction to Statistical Learning
  • Springer, Gareth James/Daniela Witten/Trevor Hastie/Robert Tibshirani
  • "ISL". I used in Columbia University machine learning classes.
• The Elements of Statistical Learning
  • Springer, Trevor Hastie/Robert Tibshirani/Jerome Friedman
  • "ESL". I used in Columbia University machine learning classes.
• Practical Statistics for Data Scientists
  • O'REILLY, Peter Bruce
  • A/B testing
• Machine Learning Design Patterns
  • O'REILLY, Valliappa Lakshmanan
• Mathematical Methods in the Physical Sciences
  • Mary L Boas
  • Linear algebra and calculus
• Introduction to Linear Algebra
  • Gilbert Strang, Wellesley-Cambridge Press
  • Introduction to Linear Alg ebra, Fifth Edition (2016)
  • Graduate students textbook

Coursera

• Deep Learning Specialization
  • Understand neural network
• Mathematics for Machine Learning Specialization
  • Understand linear algebra
• Machine Learning
  • Support vector machine
  • By Andrew Ng

Udemy

• Complete linear algebra: theory and implementation in code
  • Principal component analysis
  • Least-squares
  • Eigendecomposition
  • Singular value decomposition
• Master statistics & machine learning: intuition, math, code
  • Traditional statistics basics

Website

• Machine Learning Mastery
• 3Blue1Brown
  • Series of videos developing mathematical intuition

Video

• StatQuest
• 3Blue1Brown
  • Series of videos developing mathematical intuition

Data

• kaggle
• Imbalance class data
  • Credit card fraud detection
• Elements of statistical learning data
• web_page_data.csv
  • Web page session time data from O'REILLY Practical Statistics for Data Scientists

Paper

Topic	Title	Link
XGBoost	XGBoost: A Scalable Tree Boosting System	https://arxiv.org/abs/1603.02754

Action items

• Review boosting
• Review Gini and Entropy (2021-12-19)
• Review KNN
• Review calibration
• Kaggle credit card fraud detection
• Read ISL 10.3.1 K-Means Clustering
• Read ISL 10.3.2 Hierarchical Clustering
• Read ISL from 9.2 Support Vector Machines
• Read XGBoost paper
• Read SMOTE paper
• Coursera Mathematics for Machine Learning: Linear Algebra
  • Didn't understand week 5 calculating eigenvectors
• ESL 3.1 and 3.2
• ESL 4.3 Linear Discriminant Analysis
• Read ESL from 5.5 Automatic Selection of the Smoothing Parameters
• Read ESL from 10.10.3 Implementation of Gradient Boosting
• Read ESL from 11.5.2 Overfitting
• Check AB testing
  • https://www.kaggle.com/tammyrotem/ab-tests-with-python