INF ML AI
Information, machine learning and AI related cards.
- Sum of Gaussian random variables
- Naive, safe and online softmax
- Pytorch's Module class
- Pytorch's nn.init functionality
- Negative log likelihood loss. A perspective.
- Harris corner detector
- Inverse of symmetric matrix is symmetric
- On model invariant performance
- Activation functions
- Attention layer
- Sinusoidal positional embedding
- Transformer implementation
- Gompertz distribution
- Edward Zang's stride visualizer
- Projectile arc visualization for Jensen's inequality
- Summand on Entropy
- Adam optimizer
- What are we doing in science?
- Layer norm
- What are we doing in science?
- Jacobian and Hessian
- Importance sampling and rejection sampling
- Monte Carlo Methods
- ELBO via Jensen
- Covariance matrix and estimation
- Chi-squared distribution
- Binomial distribution. A perspective.
- Random number generation in Numpy
- Characterizing a surface's "color" properties
- Color perception
- Correlated color temperature (CCT)
- Standard illuminants
- Accuracy, precision, recall
- Auto-encoder (VAE?) [stub]
- Latent variables in autoencoders
- Richard–Berry paradox
- The two types of compressors
- Covariance matrix
- Multivariate Gaussian distribution
- Gaussian distribution
- Belief Networks (by Koller)
- Compression and modularity of probabilistic models
- Motivation for graphical models
- Belief networks
- Belief networks: independence
- Belief networks: independence
- Belief networks: independence examples
- How many parameters are needed to describe this distribution?
- The urns
- Logistic regression LED exercise
- Kraft inequality
- Symbol codes
- Jensen's inequality
- Kullback-Leibler divergence and Gibbs' inequality
- Entropy of an ensemble
- Joint entropy of two random variables
- Shannon information content
- What is the derivative of negative log MLE (MLE used as a negative cost) when the variables are passed through softmax activations?
- Softmax
- Incremental average (estimate update)
- Cross-Entropy and KL divergence
- Entropy
- Maximum likelihood estimation (MLE)
- Types of machine learning tasks
- Logistic sigmoid
- Rectifier and the softplus function
- Bernoulli Distribution
- Covariance
- Independence & Conditional Independence
- Machine Learning Definition (Mitchell, 1997)
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