Posts
2025
Perceptron 101: Regression from Neural Network FoundationsDecember 21, 2025
Calculus 103: Optimization Using Gradient Descent in Two VariablesDecember 20, 2025
Calculus 102: Optimization Using Gradient Descent in One VariableDecember 19, 2025
Calculus 101: Differentiation in PythonDecember 18, 2025
Linear Algebra 201December 17, 2025
Linear Algebra 106December 16, 2025
Linear Algebra 105: Matrix MultiplicationDecember 15, 2025
Linear Algebra 104: Vector OperationsDecember 14, 2025
Linear Algebra 103December 13, 2025
Linear Algebra 102December 12, 2025
Linear Algebra 101December 11, 2025
Torch 402: Saliency Maps and Grad-CAMDecember 10, 2025
Torch 401: Visualizing and Interpreting CNNsDecember 9, 2025
Torch 302: EmbeddingsDecember 8, 2025
Torch 301: Basic TokenizationDecember 7, 2025
Torch 203: Pre-trained Models and Visual InferenceDecember 6, 2025
Torch 202: TorchVision DatasetsDecember 5, 2025
Torch 201: TorchVision for Pre-ProcessingDecember 4, 2025
Torch 103: Debugging, Modularizing, and Inspecting ModelsDecember 3, 2025
Torch 102: Activation Functions Meet Delivery RealityDecember 2, 2025
Torch 101: One Neuron, Real InsightsDecember 1, 2025
CI 201: Introduction to Causal Inference with PPLsNovember 30, 2025
Gauss 301: Laplace ApproximationNovember 29, 2025
Gauss 203: Linear Combinations in 2D GaussiansNovember 28, 2025
Gauss 202: Log Probability of 2D Sample MeansNovember 27, 2025
Gauss 201: Multivariate Gaussian in Two DimensionsNovember 26, 2025
Gauss 102: Distribution of the Sample MeanNovember 25, 2025
Gauss 101November 24, 2025
PyMC 402: Gaussian ProcessesNovember 23, 2025
PyMC 401: Linear GLMs Two WaysNovember 22, 2025
PyMC 302: Dimensions Without TearsNovember 21, 2025
PyMC 301: PyTensor Graph SurgeryNovember 20, 2025
PyMC 204: Dimensionality and CoordinatesNovember 19, 2025
PyMC 203: Prior and Posterior Predictive ChecksNovember 18, 2025
PyMC 202: Bayesian Model Comparison with LOO and WAICNovember 17, 2025
PyMC 201: Advanced Topics — Custom Operations and DistributionsNovember 16, 2025
PyMC 104: Change-point modeling — Coal mining disastersNovember 15, 2025
PyMC 103: Linear Regression With Synthetic PlantsNovember 14, 2025
PyMC 102: Regularized Regression with the Horseshoe PriorNovember 13, 2025
PyMC 101: Overview and WorkflowNovember 12, 2025
PKPD_META 106: Two-Patient PKPD Workflow with Stand ODE and RStanNovember 11, 2025
PKPD Meta 105: Single-Patient Bayesian WorkflowNovember 10, 2025
PKPD Meta 104: Mapping the Gelman ODE into StanNovember 9, 2025
PKPD Meta 103: Recasting the Drug–Disease Turnover ModelNovember 8, 2025
PKPD Meta 102: Semimechanistic Turnover LogicNovember 7, 2025
PKPD Meta 101: Modeling the Modern Drug Discovery ProcessNovember 6, 2025
PKPD 104: Turnover Models for Indirect ResponseNovember 5, 2025
PKPD 103: Effect Compartment ModelsNovember 4, 2025
PKPD 102: Direct Response PD ModelsNovember 3, 2025
PKPD 101: Deriving the One-Compartment Oral ModelNovember 2, 2025
JAX 203: Probabilistic Programming with BamojaxNovember 1, 2025
JAX 202: Bayesian Sampling with BlackJaxOctober 31, 2025
JAX 201: Multi-GPU Training with pmapOctober 30, 2025
JAX 103: Vectorization with vmapOctober 30, 2025
MCMC 102: Hamiltonian Monte Carlo ChainsOctober 29, 2025
MCMC 101: Leapfrog IntegratorOctober 28, 2025
JAX 102: Control Flow with laxOctober 27, 2025
JAX 101October 26, 2025
Function Tools 101October 25, 2025
Stan 103: Effective Sample SizeOctober 24, 2025
Stan 102: Trusting R-hatOctober 23, 2025
Stan 101 with Logistic RegressionOctober 22, 2025
Understanding Collider Structures in DAGsOctober 16, 2025
Demystifying the Stable Unit Treatment Value AssumptionOctober 15, 2025
Demystifying the Positivity AssumptionOctober 14, 2025
Demystifying the Exchangeability AssumptionOctober 13, 2025
Causal Inference 101October 12, 2025
MCP 101October 4, 2025
Welcome to DRC LabOctober 3, 2025