General

Terms^{Chapter 1}

Training^{Chapter 4}

Resampling

Classification^{Chapter 3}

SVM^{Chapter 5}

Encoder

Scaler

Imbalanced Data

Small Data

Ensemble^{Chapter 7}

Dimensional Reduction^{Chapter 8}

Feature Engineering

Distance

Fair ML

Models

Learning Types

FAQ

End to End

Preprocessing

Checklist^{Appendix B}

Regression^{Chapter 2}

Pipeline^{Chapter 2}

Classification^{Multiple Classes}

Classification^{Binary Classes}

Regression Models

Linear Regression^{Chapter 4}

SGD Regression^{Chapter 4}

Batch GD Regression^{Chapter 4}

Mini-batch Regression^{Chapter 4}

Ridge Regression^{Chapter 4}

Lasso Regression^{Chapter 4}

Elastic Net^{Chapter 4}

k-Nearest Neighbors Regression

Decision Tree Regression

Random Forest Regression

Ada Boosting Regression

Gradient Boosting Regression

XGBoost Regression

Support Vector Regression^{Chapter 5}

Classification Models

SGD Classifier

Decision Tree Classifier

Random Forest Classifier

Extra Trees Classifier

Ada Boosting Classifier

Gradient Boosting Classifier

Logistic Regression^{Chapter 4}

Softmax Regression^{Chapter 4}

Naive Bayes Classifier

SVM^{Chapter 5}

k-Nearest Neighbors

LightGBM

XGBoost Classifier

Unsupervised Models

GMM^{Chapter 9}

Clustering^{Chapter 9}

Kernel Density Estimation (KDE)

Original Model^{Anomaly Detection}

Multivariate Model^{Anomaly Detection}

Semi-Supervised Learning

Multi-Output

KNN Classifier

Linear Regression

RidgeCV

KNN Regressor

Extra Trees Regressor

DecisionTreeRegressor

Projects

Kickstarter

California Housing Price

Titanic Dataset

Spam Email Classifier

MNIST KNN

Bank Note Authentication^PU

Scikit Learn

Common Terms

API

Gaussian Processes

Cross Decomposition

Naive Bayes

Decision Tree^{Chapter 6}

Ensemble Learning^{Chapter 7}

Multioutput

Feature Selection

Semi-Supervised Learning

Supervised NN

GMM^{Chapter 9}

Clustering^{Chapter 9}

Biclustering

Covariance Estimation

Anomaly Detection^{Chapter 9}

Density Estimation

Unsupervised NN

Metrics

Curves

Scoring

Feature Extraction

Dimension Reduction^{Chapter 8}

Classifiers

Face completion

Generative Models

Kernel Density Estimation (KDE)

Time-Series

Introduction^{Chapter 1}

Exponential Smoothing

Analysis^{Chapter 2}

Pandas Time Series

Sktime

Deep Learning

GAN

AutoML

Intro

dabl

auto-sklearn

Visualization

Pandas Plot

Yellowbrick

Dataset

OpenML

UCI Machine Learning Respository

Kaggle Datasets

Amazon's AWS Datasets

Public Datasets

MATLAB data sets

Data Portals

Open Data Monitor

Quandl

Wiki List

Quora

Reddit

Online Platform

Kaggle

Google Colab

Seedbank

Courses

Data Mining and Text Mining^UIC

Machine Learning^{Adrew Ng}

People

Geoffrey E. Hinto

Books

Practical Econometrics

Forecasting: Principles and Practice

Machine Learning for Time-Series with Python

Engineer Statistics

Python Data Science Handbook

Hands-on Notebook 2

Hands-on Notebook

Others

Tensorflow Certificate

Main Types of Neural Networks

Generalized N-body Problems

Nearest Neighbor

Reference

A.I. Wiki

MIT AI

Scikit User Guide

Scikit Tutorial

Google Colab

Kaggle Tutorial

Kaggle Learn

Statistics

Deep Learning Repositories

Bloomberg

Machine Learning Mastery

15-hours Machine Learning

Intro to Statistical Learning

The Elements of Statistical Learning

Machine Learning Mastery

Data Science Central

Dataquest Tutorials

Deeplearning.net

Towards Data Science

AstroML