Discover Top Change & Prediction Model Articles for AI and Data Science

Change Models

Model 12: Difference Equation – Farm Problem

Model 13: Difference Equation – Weight‑Loss Problem

Model 14: Difference Equation – Discrete Logistic Growth Model

Model 15: Difference Equation – Yeast Growth

Model 16: Difference Equation – Chromosome Inheritance Model

Model 17: Differential Equation – Drug Distribution in the Body

Model 18: Differential Equation – Inter‑species Competition

Model 18: Differential Equation – Population Competition

Prediction Models

2.1 Time Series

Model 18: Concept of Time Series

Model 20: Exponential Smoothing Method

Model 21: Seasonal Time Series Forecasting

Model 22: Stationary Time Series Concept

Model 23: ARMA

Model 24: ARMA Model Construction

Model 25: ARMA Forecasting

Model 26: ARMA Model Solution in Python

Model 27: Non‑Stationary Time Series

Model 55: Identification of Stationary Random Time Series

Model 56: Testing of Stationary Random Time Series

Model 58: Vector Autoregression (VAR)

Model 59: Prophet Model (with Python code)

2.2 Machine Learning

Model 28: Overview of Machine Learning

Model 30: Machine Learning Process, Types, and Applications

Model 31: Machine Learning Journey

Model 32: Supervised Learning Examples

Model 33: Support Vector Machine – Basic Principles and Linear Separability

Model 34: Generalized Linear Separable SVM

Model 35: Non‑Linear Separable SVM

Model 36: Support Vector Regression

Model 37: SVM Applications

Model 38: Artificial Neural Network – Overview

Model 41: Ten Key Concepts and Charts in Machine Learning

Model 43: Deep Learning – Implementing Multilayer Perceptron with Keras

Model 44: Deep Learning – Building Regression MLP with Keras Sequential API

Model 50: Deep Learning – Convolutional Neural Networks

Model 51: Deep Learning – Recurrent Neural Networks

Model 65: Ensemble Learning Overview

Model 65: ARCH and GARCH Models for Time Series Forecasting (Python)

Model 66: Ensemble Learning – AdaBoost Principle

Model 66: XGBoost Implementation (Python)

Model 67: LightGBM Implementation (Python)

Model 68: LSTM Theory and Implementation

Model 69: Bayesian Personalized Ranking (BPR) Algorithm

Model 69: LSTM Practical – Air Pollution Prediction

Model 70: SimRank Collaborative Filtering Recommendation

Model 70: Using Scikit‑Learn to Impute Missing Values

2.3 Grey Prediction

Model 12: Concept of Grey Prediction Model

Model 13: GM(1,1) Grey Prediction Model

Model 15: GM(1,N) Grey Prediction Model

Model 16: GM(1,N) Grey Prediction Example (with Python code)

Model 17: GM(2,1) Grey Prediction Model (with Python code)

More model articles can be found in the original source’s other posts.