This easy-to-use reference for TensorFlow 2 design patterns in
Python will help you make informed decisions for various use cases.
Author KC Tung addresses common topics and tasks in enterprise data
science and machine learning practices rather than focusing on
TensorFlow itself. When and why would you feed training data as
using NumPy or a streaming dataset? How would you set up
cross-validations in the training process? How do you leverage a
pretrained model using transfer learning? How do you perform
hyperparameter tuning? Pick up this pocket reference and reduce the
time you spend searching through options for your TensorFlow use
cases. Understand best practices in TensorFlow model patterns and
ML workflows Use code snippets as templates in building TensorFlow
models and workflows Save development time by integrating prebuilt
models in TensorFlow Hub Make informed design choices about data
ingestion, training paradigms, model saving, and inferencing
Address common scenarios such as model design style, data ingestion
workflow, model training, and tuning
General
Imprint: |
O'Reilly Media
|
Country of origin: |
United States |
Release date: |
July 2021 |
Authors: |
Kc Tung
|
Dimensions: |
178 x 108 x 19mm (L x W x T) |
Format: |
Paperback
|
Pages: |
300 |
ISBN-13: |
978-1-4920-8918-6 |
Categories: |
Books
Promotions
|
LSN: |
1-4920-8918-4 |
Barcode: |
9781492089186 |
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