Machine Learning

1 Shapley Value

#Basics #Interpretability

1 Neural ODE

#Deep Learning #Neural ODE

The concepts and ideas of neural ODE

1 An Introduction to Generative Models

#Self-supervised Learning #Generative Model #Basics

Discriminative model: The conditional probability of class label on data (posterior) $p(C_k\mid x)$ …

1 Contrastive Model

#Self-supervised Learning #Contrastive Model #Basics

Contrastive models learn to compare1. Contrastive use special objective functions such as [[NCE]] …

1 GAN

#Self-supervised Learning #Adversarial Model #GAN #Basics

The task of GAN is to generate features $X$ from some noise $\xi$ and class labels $Y$, $$\xi, Y \to …

1 Receiver Operating Characteristics: ROC

#Machine Learning #Performance #Basics

ROC is used to judging the performance of classifiers

1 Tree-based Learning

#Classification #Supervised Learning #Statistical Learning #Basics #Decision Tree

Tree-based learning

1 Embedding

#Machine Learning #Embedding

1 Factorization

#Machine Learning #Factorization #Tensor

1 Feature Engineering

#Machine Learning #Feature Engineering

Feature engineering is crucial to the performance of our mdoel.

1 Naive Bayes

#Machine Learning #Classification #Bayesian

Naive Bayes

1 Confusion Matrix (Contingency Table)

#Statistical Learning #Basics #Learning Metrics #Classification

Confusion Matrix It is much easier to understand the confusion matrix if we use a binary …

1 Linear Methods

#Classification #Supervised Learning #Statistical Learning #Basics #Linear Models

linear methods

1 Machine Learning Overview

#Statistical Learning #Machine Learning #Basics

A brief overview of machine learning

2 Contrastive Model: Context-Instance

#Self-supervised Learning #Contrastive Model #Mutual Information #Basics

In contrastive methods, we can manipulate the data to create data entries and infer the changes …

2 f-GAN

#Self-supervised Learning #Adversarial Model #GAN #Basics

The essence of [[GAN]] GAN The task of GAN is to generate features $X$ from some noise $\xi$ and …

2 Generative Model: Autoregressive Model

#Self-supervised Learning #Generative Model #Autoregressive Model #Basics

An autoregressive (AR) model is autoregressive, $$ \begin{equation} \log p_\theta (x) = \sum_{t=1}^T …

2 Poisson Regression

#Basics #Linear Models

Poisson regression is a generalized linear model for count data. To model a dataset that is …

2 Data Types and Level of Measurement in Machine Learning

#Machine Learning #Feature Engineering #Statistics #Data Types #Basics

identifying the data types and level of measurement is important in data science

2 Decision Tree

#Decision Tree #Supervised Learning #Statistical Learning #Basics

In this article, we will explain how decision trees work and build a tree by hand. The code used in …