How Can Machine Learning--especially Deep Neural Networks--make A Real Difference In Your Organization? This Hands-on Guide Not Only Provides Practical Information, But Helps You Get Started Building Efficient Deep Learning Networks. The Authors Provide The Fundamentals Of Deep Learning--tuning, Parallelization, Vectorization, And Building Pipelines--that Are Valid For Any Library Before Introducing The Open Source Deeplearning4j (dl4j) Library For Developing Production-class Workflows. Through Real-world Examples, You'll Learn Methods And Strategies For Training Deep Network Architectures And Running Deep Learning Workflows On Spark And Hadoop With Dl4j.--
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Fern Park |
49-12-4 |
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