Description
Deep Learning Pipeline: Building a Deep Learning Model with TensorFlow provides a step-by-step guide to building and deploying AI models using the TensorFlow and Keras frameworks. The author has attempted to transform the concept of a “pipeline” from a theoretical discussion to a practical skill that developers can use to systematically manage real-world projects.
Emphasizing practical aspects such as data preparation, choosing the right model architecture, and debugging, this text will teach the reader how to design an engineered and optimized path from the initial stages of data collection to the final stage of model deployment that is resilient to the common challenges of data-driven projects.
Book Features
- Practical training on working with the powerful TensorFlow 2.x and Keras libraries.
- Focus on modern data engineering concepts instead of old and outdated theories.
- Provide example-based instructions to better understand image and text processing steps.
- A comprehensive guide to troubleshooting and optimizing models to achieve the highest accuracy.
- Suitable for data scientists and developers who plan to participate in global competitions like Kaggle.
Book specifications
- Publisher: Apress
- Instructor/Author: Hisham El-Amir
- Number of pages: 563
- Number of seasons: 4
- Format: PDF
Headlines Deep Learning Pipeline: Building a Deep Learning Model with TensorFlow
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User Guide
Extract the file and run it with the appropriate software.
Download link
File(s) password: www.downloadly.ir
File size
8.7 MB
