Following are the list of interactive and animated visual explanations of various machine learning algorithms and concepts grouped together concept-wise in no order.
Pictures are worth a thousand words and I feel strongly these interactive visualizations and animations are worth a thousand images.
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If you are a beginner like to get better intuition about a concept
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If you are a trainer looking for a better way to explain a concept.
This list is not following any order. You can use this as a reference place to look for interactive visualization to understand or let others understand a particular concept.
- Basic Probability
- Compound Probability
- Conditional Probability
- Probability Distributions
- Bayesian Inference
- Central limit theorem
- Monty hall problem
- Basic probability concepts
- Statistics Demonstrations
- Frequentist Inference
- Comparing Mean median and mode
- Measures of Central tendency
- Basic statistics concepts
- Kernel density estimation
- Derivates visualization
- Derivatives definition
- Derivatives without words
- Basic calculus concepts
- Fourier transforms
- Eigen values and Eigen vectors
- Basic algebra concepts
- matrixmultiplication
- Invitation to another dimension
- Immersive linear algebra
- Matrix decomposition
- A Visual and Interactive Guide to the Basics of Neural Networks
- A Visual And Interactive Look at Basic Neural Network Math
- Back Propagation Math flow
- Animated demo
- Tensorflow Playground
- NN 3D Simulation
- Neural network zoo
- Parameter optimization
- Initializing neural networks
- Neural network architecture builder
- CNN Visualization video
- Image kernels
- CNN 3D Simulation
- MNIST 3D Visualization
- Convolutional layer
- Maxpooling layer
- keras.js
- convnet.js
- CNN Explainer
- LeNet style architecture builder
- AlexNet style architecture builder
- Animated RNN and LSTM
- illustrated-word2vec
- Glove demo
- illustrated-transformer
- illustrated-bert
- a-visual-guide-to-using-bert-for-the-first-time
- visualizing-neural-machine-translation-mechanics-of-seq2seq-models-with-attention
- illustrated-gpt2
- recurrentjs
- visual-numpy
- gentle-visual-intro-to-data-analysis-python-pandas
- visualizing-pandas-pivoting-and-reshaping
- Model tuning and the Bias-variance tradeoff
- L2 Regularization
- explorables
- Explained visually
- Seeing Theory
- distill pub
- jalammar github
- desmos
- geogebra
- Collection of Interactive Machine learning examples
- Teachable Machine learning
- AI notes
Feel free to give a pull request if you like to add any visualizations that I had missed.
I hope it helps! Connect with me here !