Library of Python scripts for tools and operations in various software used in my workflows. - morphingdesign/pythonLib
2D Matrix: capitalize variable names
- Case: features
1D Vector: lowercase variable names
- Case: labels
Sequential Model Considerations
Train / Test Sets
Decrease the test size for smaller overall data sets. (~25%) otherwise aim for ~33%.
If not specified, the default batch size is 32. When training model with verbose, output displays batch number rather than each training feature.
tf.keras.Sequential | TensorFlow Core v2.4.1
Sequential groups a linear stack of layers into a tf.keras.Model.
Example workflow using the Iris classification problem.
Custom training: walkthrough | TensorFlow Core
This guide uses machine learning to categorize Iris flowers by species. It uses TensorFlow to: Build a model, Train this model on example data, and Use the model to make predictions about unknown data. This guide uses these high-level TensorFlow concepts: This tutorial is structured like many TensorFlow programs: Import and parse the dataset.
Errors with this notification could be a result of the global variable initializer not being run or being run before a variable is created.