Getting to grips with deep learning techniques through frameworks such as Keras and Tensorflow means software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, author Douwe Osinga shows how to solve deep-learning problems for classifying and generating text, images, and music. Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Examples are written in Python with code available on GitHub as a set of Python notebooks.
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Author: Douwe Osinga Publisher: O'Reilly Date: June 2018 Pages: 252 ISBN: 978-1491995846 Print: 149199584X Kindle: B07DK1ZZXT Audience: developers interested in deep learning Level: Intermediate Category: Artificial Intelligence
- Create applications that will serve real users
- Use word embeddings to calculate text similarity
- Build a movie recommender system based on Wikipedia links
- Learn how AIs see the world by visualizing their internal state
- Build a model to suggest emojis for pieces of text
- Reuse pretrained networks to build an inverse image search service
- Compare how GANs, autoencoders and LSTMs generate icons
- Detect music styles and index song collections
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