- Points Appearing in Graph that are Not in the Dataset https://en.wikipedia.org/wiki/Likelihood_function 2 comments rstats
- Bayes' Theorem Applied To Coin Toss https://en.wikipedia.org/wiki/Likelihood_function 6 comments statistics
Linking pages
- Who Wrote The ‘Death Note’ Script? · Gwern.net http://www.gwern.net/Death%20Note%20script 79 comments
- Bayesian Inference and the bliss of Conjugate Priors | Sudeep Raja http://sudeepraja.github.io/Bayes/ 11 comments
- Dimensions and Haskell: Singletons in Action https://serokell.io/blog/dimensions-haskell-singletons 11 comments
- When Should I Check The Mail? · Gwern.net http://www.gwern.net/Mail-delivery 6 comments
- "greta playground" - p. bhogale https://theclarkeorbit.github.io/greta-playground.html#greta-playground 3 comments
- Experiments, Peeking, and Optimal Stopping | by Matteo Courthoud | Towards Data Science https://towardsdatascience.com/experiments-peeking-and-optimal-stopping-954506cec665 1 comment
- When Should I Check The Mail? · Gwern.net https://www.gwern.net/Mail%20delivery 0 comments
- Training Compact Transformers from Scratch in 30 Minutes with PyTorch | by Steven Walton | PyTorch | Medium https://medium.com/pytorch/training-compact-transformers-from-scratch-in-30-minutes-with-pytorch-ff5c21668ed5 0 comments
- Log Loss Function Explained by Experts | Dasha.AI https://dasha.ai/en-us/blog/log-loss-function 0 comments
- Can You Trust Your Model’s Uncertainty? – Google AI Blog https://ai.googleblog.com/2020/01/can-you-trust-your-models-uncertainty.html 0 comments
- A Gentle Introduction to Logistic Regression With Maximum Likelihood Estimation - MachineLearningMastery.com https://machinelearningmastery.com/logistic-regression-with-maximum-likelihood-estimation/ 0 comments
- Statistical Notes · Gwern.net https://www.gwern.net/Statistical-notes#oh-deer-could-deer-evolve-to-avoid-car-accidents 0 comments
- Introducing roboCap: An automated horse race handicapper - inpredictable http://www.inpredictable.com/2018/11/introducing-robocap-automated-horse.html 0 comments
- Improving Out-of-Distribution Detection in Machine Learning Models – Google AI Blog https://ai.googleblog.com/2019/12/improving-out-of-distribution-detection.html 0 comments
- Rohan & Lenny #1: Neural Networks & The Backpropagation Algorithm, Explained | by Rohan Kapur | A Year of Artificial Intelligence https://medium.com/a-year-of-artificial-intelligence/rohan-lenny-1-neural-networks-the-backpropagation-algorithm-explained-abf4609d4f9d#.7mwcjuftn 0 comments
- Dismantling pseudo-skepticism - by Felipe Contreras https://felipec.substack.com/p/dismantling-pseudo-skepticism 0 comments
- Interpretable time-series modelling using Gaussian processes - Trent Henderson https://hendersontrent.github.io/posts/2024/05/gaussian-process-time-series/ 0 comments
- blog.alexalemi.com KL is All You Need https://blog.alexalemi.com/kl-is-all-you-need.html 0 comments
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