Machine Learning Simulators

AdaBoost Simulator — Boosting Weak Classifiers

Machine Learning

AdaBoost Simulator — Boosting Weak Classifiers focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters…

Adam Optimizer Simulator

Machine Learning

Adam Optimizer Simulator compares how nearby design assumptions and key metrics shifts as the main assumptions change.

1D Linear Autoencoder Simulator — Compression Equivalent to PCA

Machine Learning

1D Linear Autoencoder Simulator — Compression Equivalent to PCA compares how statistical or numerical assumptions and sensitivity shifts as the main assumptions change.

Batch Normalization Simulator

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Bias-Variance Tradeoff Simulator

Machine Learning

Bias-Variance Tradeoff Simulator compares how nearby design assumptions and key metrics shifts as the main assumptions change.

Collaborative Filtering Simulator

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Confusion Matrix Metrics Simulator

Machine Learning

Confusion Matrix Metrics Simulator updates live numeric results and charts as inputs change, supporting early design checks and model review.

Cross-Entropy vs MSE Loss Simulator

Machine Learning

Use this page to relate representative assumptions to nearby design assumptions and key metrics before moving into the adjacent engineering checks.

k-Fold Cross-Validation Simulator

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

DBSCAN Simulator — Density-Based Clustering

Machine Learning

DBSCAN Simulator — Density-Based Clustering compares how nearby design assumptions and key metrics shifts as the main assumptions change.

Decision Analysis & Expected Value Calculator — EMV & Decision Tree

Machine Learning

Calculate Expected Monetary Value (EMV) and visualize decision trees. Use our tool for probability distributions and tornado sensitivity analysis in decision-making.

Decision Tree Impurity — Gini, Entropy and Misclassification

Machine Learning

Decision Tree Impurity — Gini, Entropy and Misclassification compares how nearby design assumptions and key metrics shifts as the main assumptions change.

Dropout Regularization Simulator

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Elastic Net Regression Simulator

Machine Learning

Elastic Net Regression Simulator focuses on statistical or numerical assumptions and sensitivity, giving a compact read on the current case and the trend that matters ne…

Gaussian Process Regression — RBF Kernel & 95% Confidence Band

Machine Learning

Gaussian Process Regression — RBF Kernel & 95% Confidence Band focuses on statistical or numerical assumptions and sensitivity, giving a compact read on the current case…

Genetic Algorithm Optimizer

Machine Learning

Run GA optimization on Rastrigin, Ackley, Sphere, and Rosenbrock functions. Watch population evolve on fitness landscape.

Gradient Boosting Simulator

Machine Learning

Use this page to relate representative assumptions to nearby design assumptions and key metrics before moving into the adjacent engineering checks.

Gradient Clipping Simulator

Machine Learning

Gradient Clipping Simulator compares how nearby design assumptions and key metrics shifts as the main assumptions change.

Gradient Descent with Momentum Simulator

Machine Learning

Use this page to relate representative assumptions to nearby design assumptions and key metrics before moving into the adjacent engineering checks.

Gradient Descent Optimizer Visualizer — SGD, Adam, RMSprop

Machine Learning

Visualize how SGD, Adam, and RMSprop navigate 2D loss landscapes in real time. Understand machine learning optimization algorithms interactively.

Hierarchical Clustering Simulator — Agglomerative & Dendrogram

Machine Learning

Hierarchical clustering simulator with live dendrogram. Switch single/complete/average linkage and cut at a distance threshold to control cluster count.

Image Convolution Kernel Simulator

Machine Learning

Use this page to relate representative assumptions to control response, stability margin, and tuning assumptions before moving into the adjacent engineering checks.

K-Fold Cross-Validation Simulator — Polynomial Degree Selection

Machine Learning

The K-fold cross-validation simulator fits polynomials to 1D data and picks the best degree by K-fold CV. Compare train MSE and CV MSE to see when overfitting starts.

k-Means Clustering Simulator

Machine Learning

k-Means Clustering Simulator focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters next.

k-NN 2D Classifier Simulator — Decision Boundary and LOO Accuracy

Machine Learning

k-NN 2D Classifier Simulator — Decision Boundary and LOO Accuracy compares how nearby design assumptions and key metrics shifts as the main assumptions change.

Kriging Surrogate Model (Gaussian Process Regression) Simulator

Machine Learning

Use this page to relate representative assumptions to vibration or acoustic response and frequency behavior before moving into the adjacent engineering checks.

Learning Curve Simulator — Diagnose Overfitting & Underfitting

Machine Learning

Use this page to relate representative assumptions to electromagnetic, circuit, and transmission conditions before moving into the adjacent engineering checks.

Learning Rate Schedule Simulator

Machine Learning

Learning Rate Schedule Simulator focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters next.

Linear SVM Simulator — Soft-Margin 2D Classification

Machine Learning

Train a linear SVM on 2D data via subgradient descent. Visualize the maximum-margin hyperplane, support vectors and the hinge-vs-L2 tradeoff controlled by C.

Logistic Regression (2D Binary Classifier) Simulator

Machine Learning

A focused entry point for statistical or numerical assumptions and sensitivity, useful before selecting the next tool in the same cluster.

Gaussian Naive Bayes Classifier Simulator — 2D, 3 Classes

Machine Learning

Visualize log-posteriors and decision boundaries of a 2D, three-class Gaussian Naive Bayes classifier. Move the query point, shift sigma and resample to see the effect.

Neural Network Visualizer — Forward & Backpropagation in Real Time

Machine Learning

Visualize and train neural networks in real time. Learn how forward propagation and backpropagation solve the XOR problem with interactive examples.

Principal Component Analysis (PCA) Simulator — Eigendecomposition for 2D Data

Machine Learning

Visualize PCA on correlated 2D data in real time. Eigendecomposition of the 2x2 covariance matrix yields principal axes and explained variance ratios.

Perceptron Learning Simulator — Linear Classifier Convergence

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Policy Gradient Simulator

Machine Learning

Policy Gradient Simulator compares how environmental or chemical-process balance and operating margin shifts as the main assumptions change.

Pooling Layer Simulator — CNN

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Q-Learning Simulator — Reinforcement Learning Gridworld

Machine Learning

A focused entry point for nearby design assumptions and key metrics, useful before selecting the next tool in the same cluster.

Random Forest Majority Vote — Bagging and Variance Reduction

Machine Learning

Use this page to relate representative assumptions to nearby design assumptions and key metrics before moving into the adjacent engineering checks.

L1/L2 Regularization Simulator — Lasso vs Ridge

Machine Learning

L1/L2 Regularization Simulator — Lasso vs Ridge focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matter…

Softmax and Cross-Entropy Loss — Core of Classification

Machine Learning

The Softmax and cross-entropy loss simulator turns three-class logits and a temperature parameter into a probability distribution and loss value in real time.

Spectral Clustering Simulator

Machine Learning

Spectral Clustering Simulator focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters next.

Stochastic Gradient Langevin Dynamics (SGLD) Simulator

Machine Learning

Stochastic Gradient Langevin Dynamics (SGLD) Simulator focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that…

TF-IDF Vectorizer Simulator

Machine Learning

TF-IDF Vectorizer Simulator focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters next.

Transformer Attention Basics Simulator

Machine Learning

Use this page to relate representative assumptions to nearby design assumptions and key metrics before moving into the adjacent engineering checks.

Weight Initialization Simulator — Xavier & He

Machine Learning

Weight Initialization Simulator — Xavier & He focuses on nearby design assumptions and key metrics, giving a compact read on the current case and the trend that matters …