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--- clase:iabd:pia:documentacion [2024/05/09 12:41]
admin [Probabilidad del resultado de la red]
+++ clase:iabd:pia:documentacion [2024/12/14 20:39] (actual)
admin [Pipelines , MLOps]
@@ Línea 127: / Línea 127: @@
   * [[https://towardsdatascience.com/probability-learning-ii-how-bayes-theorem-is-applied-in-machine-learning-bd747a960962|Probability Learning II: How Bayes’ Theorem is applied in Machine Learning]]
   * {{ :clase:iabd:pia:a_gentle_introduction_to_bayesian_analysis.applications_to_development_research.pdf|A Gentle Introduction to Bayesian Analysis.Applications to Development Research}}
+  * [[https://en.wikipedia.org/wiki/Pre-_and_post-test_probability|Pre- and post-test probability]]
@@ Línea 148: / Línea 148: @@
   * [[https://medium.com/analytics-vidhya/colab-vs-code-github-jupyter-perfect-for-deep-learning-2b257ae94d01|Colab + Vs Code + GitHub + Jupyter (Perfect for Deep Learning)]]
   * [[https://www.tensorflow.org/guide/keras/save_and_serialize|Guardando y Serializando Modelos con TensorFlow Keras]]
+  * [[https://365datascience.com/tutorials/machine-learning-tutorials/how-to-deploy-machine-learning-models-with-python-and-streamlit/|How to Deploy Machine Learning Models with Python & Streamlit]]

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