Deep Learning Cookbook - by Douwe Osinga (Paperback)
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<p/><br></br><p><b> About the Book </b></p></br></br>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.<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>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.</p><p>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.</p><p>You'll learn how to: </p><ul><li>Create applications that will serve real users</li><li>Use word embeddings to calculate text similarity</li><li>Build a movie recommender system based on Wikipedia links</li><li>Learn how AIs see the world by visualizing their internal state</li><li>Build a model to suggest emojis for pieces of text</li><li>Reuse pretrained networks to build an inverse image search service</li><li>Compare how GANs, autoencoders and LSTMs generate icons</li><li>Detect music styles and index song collections</li></ul><p/><br></br><p><b> About the Author </b></p></br></br><p>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).</p>
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