Maximum Likelihood Estimation - how neural networks learn | Chan`s Jupyter

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Maximum Likelihood Estimation - how neural networks learn | Chan`s Jupyter

In this post, we will review a Maximum Likelihood Estimation (MLE for short), an important learning principle used in neural network training. This is the copy of lecture “Probabilistic Deep Learning with Tensorflow 2” from Imperial College London.

https://goodboychan.github.io/python/coursera/tensorflow_probability/icl/2021/08/19/01-Maximum-likelihood-estimation.html

[AlexTech123]

Thanks for this very usefull article!!!