Machine Learning Models
Explore various machine learning algorithms through interactive visualizations and comprehensive explanations. Select a model category to begin your learning journey.
Supervised Learning
Models that learn from labeled training data
Regression Models
Predict continuous values
Linear Regression
Learn how linear regression works and how to implement it
Polynomial Regression
Extend linear models to capture non-linear relationships
Ridge & Lasso Regression
Regularization techniques to prevent overfitting
Classification Models
Predict categorical values
Logistic Regression
Understand the mathematics of logistic regression
Decision Trees
Understand decision trees and their applications
Support Vector Machines
Explore the mathematics behind SVMs
Random Forests
Learn how ensemble methods improve performance
K-Nearest Neighbors (KNN)
A simple yet effective classification algorithm
Unsupervised Learning
Models that find patterns in unlabeled data
Clustering Algorithms
Group similar data points together
K-Means Clustering
Explore how K-means partitions data into clusters
Hierarchical Clustering
Understand how hierarchical clustering works
Dimensionality Reduction
Reduce the number of features while preserving information
Principal Component Analysis
Learn how PCA transforms high-dimensional data
Neural Networks
Deep learning models inspired by the human brain
Basic Neural Networks
Understand the fundamentals of neural networks
Multilayer Perceptron
Learn about the building blocks of deep learning
Specialized Neural Networks
Neural networks designed for specific data types
Convolutional Neural Networks
Visualize how CNNs process images
Recurrent Neural Networks
See how RNNs handle sequential data
Transformers
Explore the architecture behind modern NLP models
Model Comparison
Not sure which model to choose? Compare different machine learning models across various metrics and use cases.
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