A01=Douwe Osinga
adversarial networks
AI artificial intelligence deep learning
Author_Douwe Osinga
Category=UMZ
classification
dimensionality
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
image similarity
iPython Jupyter notebooks
Keras
machine learning in production
natural language processing
Postgres
Python
recommendation systems
recommenders
recurrent neural networks
RNN
text generation
visualization
Product details
- ISBN 9781491995846
- Weight: 454g
- Dimensions: 180 x 233mm
- Publication Date: 30 Jun 2018
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
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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
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.
