The “User Interface Tour” and “Keyboard Shortcuts” are useful places to start, but there are also many other links to documentation there. Last revised: 1 by Dick Furnstahl can find valuable documentation under the Jupyter notebook Help menu. Standard medical example by applying Bayesian rules of probability Mini-project IIIb: Bayesian Neural NetworksĬhecking the sum and product rules, and their consequences Mini-project IIb: How many lines are there? Mini-project I: Parameter estimation for a toy model of an EFT Linear algebra games including SVD for PCA What is a convolutional neural network?ġ0.2. Variational Inference: Bayesian Neural Networksĩ.10. Neural network classifier demonstrationĩ.9.
#HOW TO SHOW ALL OF A MATRIX IN PYTHON JUPYTER NOTEBOOK PDF#
Making figures for Ignorance PDF notebookĩ.6. Maximum Entropy for reconstructing a function from its momentsĨ.5. Ma圎nt for deriving some probability distributionsĨ.4. Ignorance pdfs: Indifference and translation groupsĨ.3. Exercise: Gaussian Process models with GPyĨ.2.
Learning from data: Gaussian processesħ.4. zeus: Sampling from multimodal distributionsħ.3. Comparing samplers for a simple problemĦ.9. Solving orbital equations with different algorithmsĦ.8. Quick check of the distribution of normal variables squaredĦ.4. Example: Parallel tempering for multimodal distributions vs. Example: Parallel tempering for multimodal distributionsĥ.6. Evidence calculation for EFT expansionsĥ.5. Building intuition about correlations (and a bit of Python linear algebra)ĥ.3. Visualization of the Central Limit TheoremĤ.8. Error propagation: Example 3.6.2 in SiviaĤ.7. Parameter estimation example: fitting a straight line IIĤ.6. Metropolis-Hasting MCMC sampling of a Poisson distributionĤ.4. Follow-up: fluctuation trends with # of points and data errorsģ.2. Linear algebra games including SVD for PCAĢ.12. Assignment: Follow-ups to Parameter Estimation notebooksĢ.11. Amplitude of a signal in the presence of backgroundĢ.9. Linear Regression and Model Validation demonstrationĢ.8. Parameter estimation example: fitting a straight lineĢ.6. Assignment: 2D radioactive lighthouse location using MCMCĢ.5.
Parameter estimation example: Gaussian noise and averagesĢ.3. Standard medical example by applying Bayesian rules of probabilityĢ.2. Interactive Bayesian updating: coin flipping exampleġ.6. Checking the sum and product rules, and their consequencesġ.5.
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