Planned
Model Training
Experiment with architectures, hyperparameters, optimization, and model performance.
Interactive AI experiments
Understand AI by experimenting with it.
Explore interactive machine-learning labs that let you change model parameters, train algorithms, visualize predictions, and understand how AI systems learn.
11 interactive machine-learning labs · Free access · Runs in your browser
Available now · Free
Start with an experiment.
Each lab is an interactive learning resource. Change its settings, inspect the results, and build intuition one model at a time.
Model Training and Optimization
Fit linear models, tune their parameters, and explore how training changes predictions.
Classification Algorithms
Compare how different classifiers use data to draw decision regions and predict labels.
Classification
Binary Classification with Logistic Regression
Train a probability-based classifier, adjust its decision threshold, and inspect its boundary.
Open LabClassification
Decision Tree Classification
Change tree depth and split criteria to explore interpretable rules and nonlinear regions.
Open LabClassification
K-Nearest Neighbors
Adjust the number of neighbors and see how nearby examples shape classification regions.
Open LabClassification
Gaussian Naive Bayes
Explore how feature distributions and class probabilities inform predictions.
Open LabClassification
Random Forest Classification
Change the number of randomized trees and compare how their combined votes classify data.
Open LabClassification
Support Vector Machine
Adjust regularization and inspect how a maximum-margin classifier separates observations.
Open LabUnsupervised Learning
Find structure in unlabeled data by exploring cluster assignments and centroids.
Neural Networks and Dimensionality Reduction
Explore a trainable neural classifier and how principal components summarize data variation.
A practical learning loop
Learn by Experimenting
01
Configure
Change model parameters and experiment settings.
02
Observe
Run experiments and visualize predictions or model behaviour.
03
Understand
Compare outcomes and develop an intuition for how algorithms work.
Planned capabilities
Beyond Interactive Tutorials
Explore upcoming interactive environments designed to help learners experiment with advanced AI systems and understand their behaviour.
Planned
AI System Experiments
Explore embeddings, retrieval, model outputs, and evaluation workflows.
Planned
RAG Experiments
Investigate document chunking, retrieval quality, context construction, and grounded responses.
Planned
AI Evaluation
Compare outputs, evaluate quality, and understand trade-offs between system configurations.
These advanced capabilities are planned and are not available as working labs today. Subscription access is also planned; no payment or subscription is required for the 11 labs above.
Stay in the loop
Get Early Access to Advanced AI Labs
Be among the first to explore upcoming interactive environments for advanced AI experimentation.
An online signup form still needs an email-collection integration. This link opens your email app; emailing expresses interest and does not guarantee access.