Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Price: $41.32
(as of Dec 15,2024 06:18:38 UTC – Details)

ASIN ‏ : ‎ B07CB455BF
Publisher ‏ : ‎ Packt Publishing; 1st edition (August 31, 2018)
Publication date ‏ : ‎ August 31, 2018
Language ‏ : ‎ English
File size ‏ : ‎ 39308 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 823 pages

In this post, we will delve into the world of transfer learning with Python, utilizing advanced deep learning and neural network models using TensorFlow and Keras. Transfer learning is a powerful technique in the field of machine learning that allows us to leverage pre-trained models and adapt them to our specific tasks, saving time and resources in the training process.

We will cover the following topics in this hands-on tutorial:
1. Introduction to transfer learning and its benefits
2. Setting up TensorFlow and Keras for deep learning development
3. Loading pre-trained models for transfer learning
4. Fine-tuning pre-trained models for custom tasks
5. Implementing transfer learning on real-world datasets
6. Evaluating model performance and optimizing hyperparameters

By the end of this tutorial, you will have a solid understanding of transfer learning and be equipped with the skills to implement advanced deep learning models in your own projects. Let’s dive in and unlock the potential of transfer learning with Python!
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