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l1-regularization

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Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value

  • Updated Dec 22, 2021
  • Jupyter Notebook

The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

  • Updated Aug 10, 2019
  • Jupyter Notebook

Overparameterization and overfitting are common concerns when designing and training deep neural networks. Network pruning is an effective strategy used to reduce or limit the network complexity, but often suffers from time and computational intensive procedures to identify the most important connections and best performing hyperparameters. We s…

  • Updated Sep 1, 2020
  • Python
Image-Reconstructor-FISTA-proximal-method-on-wavelets-transform

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