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Hands-On Deep Learning with Apache Spark : Build and Deploy Distributed Deep Learning Applications on Apache Spark.
Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt,
2019.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 505 | 0 | |a Hands-on deep learning with Apache Spark: build and deploy distributed deep learning applications on Apache Spark -- Contributors -- Table of Contents -- Preface -- Chapter 1: The Apache Spark Ecosystem -- Chapter 2: Deep Learning Basics -- Chapter 3: Extract, Transform, Load -- Chapter 4: Streaming -- Chapter 5: Convolutional Neural Networks -- Chapter 6: Recurrent Neural Networks -- Chapter 7: Training Neural Networks with Spark -- Chapter 8: Monitoring and Debugging Neural Network Training -- Chapter 9: Interpreting Neural Network Output -- Chapter 10: Deploying on a Distributed System -- Chapter 11: NLP Basics -- Chapter 12: Textual Analysis and Deep Learning -- Chapter 13: Convolution -- Chapter 14: Image Classification -- Chapter 15: What's Next for Deep Learning? -- Appendix A: Functional Programming in Scala -- Appendix B: Image Data Preparation for Spark -- Other Books You May Enjoy -- Index. | |
| 520 | 3 | |a Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. | |
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