Sinossi
Deep learning doesnÃ?Â[ 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, youÃ?Â[ 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 youÃ?Â[ re stuck. Examples are written in Python with code available on GitHub as a set of Python notebooks.
YouÃ?Â[ 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
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
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).
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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