Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Recent developments in deep learning have put the field center stage for innovation in software engineering. New algorithms and techniques in academia hold promise for many real world problems, and new machine learning platforms are powerful, but aren’t necessarily easy to get started with.
With this hands-on cookbook, you'll discover that deep learning doesn't need to be intimidating. Aimed at readers who are new to deep learning, this cookbook enables you to solve problems quickly, using the most appropriate platform for each application. You'll learn how to leverage the work of Google by reusing pre-trained networks, use non-final layers to map data, and build recommender systems out of any correlation data.
- Work with step-by-step recipes that address familiar problems in areas such as text embeddings, text labeling and generation, and image classification and generation
- Walk through a practical solution for each recipe, using modern machine learning frameworks
- Learn how your newly-trained models can be easily ported for use in production settings
- Build applications that go from interesting results to serving real users
- Use deep learning in production, including how to query embeddings with the Postgres database, and how export and serve models using TensorFlow
- Set up a microservice using Python, and run models on mobile devices