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Joint Likelihood - Python and Machine Learning for Integrated Circuits - - An Online Book - |
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| Python and Machine Learning for Integrated Circuits http://www.globalsino.com/ICs/ | ||||||||
| Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= Joint likelihood typically refers to a statistical concept used in various fields, such as statistics, machine learning, and Bayesian inference. It represents the likelihood of observing a set of data points under a particular statistical model. In other words, it measures how well the model explains the observed data as a whole. It is used in statistical modeling, parameter estimation, or hypothesis testing. The joint likelihood can be given by,
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