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:
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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.
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Zustand: New. 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 s. Artikel-Nr. 175029413
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Taschenbuch. Zustand: Neu. Neuware - 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 not Elektronisches Buch. 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. Artikel-Nr. 9781491995846
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