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The Deep Learning with Keras Workshop
book

The Deep Learning with Keras Workshop

by Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat
July 2020
Intermediate to advanced content levelIntermediate to advanced
496 pages
9h 10m
English
Packt Publishing
Content preview from The Deep Learning with Keras Workshop

Appendix

1. Introduction to Machine Learning with Keras

Activity 1.01: Adding Regularization to the Model

In this activity, we will utilize the same logistic regression model from the scikit-learn package. This time, however, we will add regularization to the model and search for the optimum regularization parameter - a process often called hyperparameter tuning. After training the models, we will test the predictions and compare the model evaluation metrics to the ones that were produced by the baseline model and the model without regularization.

  1. Load the feature data from Exercise 1.03, Appropriate Representation of the Data, and the target data from Exercise 1.02, Cleaning the Data:

    import pandas as pd

    feats = pd.read_csv('../data/OSI_feats_e3.csv') ...

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Publisher Resources

ISBN: 9781800562967Supplemental Content