Deep Learning Cookbook - Practical recipes to get started quickly

Deep learning doesn't have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you'll learn 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. Author Douwe Osinga also provides a chapter with half a dozen techniques to help you if you're stuck. Examples are written in Python with code available on GitHub as a set of Python notebooks. You'll learn how to: 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.

Über den Autor / die Autorin

Douwe Osinga is an experienced Software Engineer, formerly with Google, and founder of three startups. He maintains a popular software project website, partly focused on machine learning(https://douweosinga.com/projects/​machine_learning).

Zusammenfassung

With the recipes in this cookbook, you’ll learn 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.

Produktdetails

• Autoren: Douwe Osinga
• Verlag: O'Reilly
• Sprache: Englisch
• Produktform: Taschenbuch
• Erschienen: 30.06.2018
• EAN: 9781491995846
• ISBN: 978-1-4919-9584-6
• Abmessung: 180 mm x 233 mm x 13 mm
• Gewicht: 454 g
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik; Software Engineering, COMPUTERS / Speech & Audio Processing, COMPUTERS / Computer Science, COMPUTERS / Mathematical & Statistical Software, COMPUTERS / Image Processing, COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Data Science / Neural Networks