From the course: Deep Learning: Model Optimization and Tuning
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Experiment setups for the course
From the course: Deep Learning: Model Optimization and Tuning
Experiment setups for the course
- In order to explore various tuning parameters and experiment with them, we have created an experiment setup. We start with a notebook called common experiment functions. In this notebook, we will use the same model for iris flower identification, that we explored in the deep learning getting started course. We first need to install the required packages for the exercises if we have already not done so. Please make sure to run this code, and check if all required dependencies are satisfied. Now let's explore the common functions that we will use throughout the course. The get data method will load up the data from iris.csv, pre-process it, extract the feature and target data sets and return them. The base model config method, initializes a set of model hyperparameters. These are the various parameters we will experiment with, in this course. For each parameter, a default value is set. During the experiment, we…
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