Run efficient deep learning models on Apache Spark using TensorFlow and KerasKey FeaturesTrain distributed complex neural networks on Apache SparkUse TensorFlow and Keras to train and deploy deep learning modelsExplore practical tips to enhance performanceBook DescriptionOrganizations these days need to integrate popular big data tools such as Apache Spark with highly efficient deep learning libraries if they’re looking to gain faster and more powerful insights from their data. With this book, you’ll discover over 80 recipes to help you train fast, enterprise-grade, deep learning models on Apache Spark.Each recipe addresses a specific problem, and offers a proven, best-practice solution to difficulties encountered while implementing various deep learning algorithms in a distributed environment. The book follows a systematic approach, featuring a balance of theory and tips with best practice solutions to assist you with training different types of neural networks such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). You’ll also have access to code written in TensorFlow and Keras that you can run on Spark to solve a variety of deep learning problems in computer vision and natural language processing (NLP), or tweak to tackle other problems encountered in deep learning.By the end of this book, you'll have the skills you need to train and deploy state-of-the-art deep learning models on Apache Spark.What you will learnSet up a fully functional Spark environmentUnderstand practical machine learning and deep learning conceptsEmploy built-in machine learning libraries within SparkDiscover libraries that are compatible with TensorFlow and KerasExplore NLP models such as word2vec and TF-IDF on SparkOrganize DataFrames for deep learning evaluationApply testing and training modeling to ensure accuracyAccess readily available code that can be reusedWho this book is forIf you’re looking for a practical resource for implementing efficiently distributed deep learning models with Apache Spark, then this book is for you. Knowledge of core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the most out of this book. Some knowledge of Python programming will also be useful.

Run efficient deep learning models on Apache Spark using TensorFlow and KerasKey FeaturesTrain distributed complex neural networks on Apache SparkUse TensorFlow and Keras to train and deploy deep learning modelsExplore practical tips to enhance performanceBook DescriptionOrganizations these days need to integrate popular big data tools such as Apache Spark with highly efficient deep learning libraries if they’re looking to gain faster and more powerful insights from their data. With this book, you’ll discover over 80 recipes to help you train fast, enterprise-grade, deep learning models on Apache Spark.Each recipe addresses a specific problem, and offers a proven, best-practice solution to difficulties encountered while implementing various deep learning algorithms in a distributed environment. The book follows a systematic approach, featuring a balance of theory and tips with best practice solutions to assist you with training different types of neural networks such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). You’ll also have access to code written in TensorFlow and Keras that you can run on Spark to solve a variety of deep learning problems in computer vision and natural language processing (NLP), or tweak to tackle other problems encountered in deep learning.By the end of this book, you'll have the skills you need to train and deploy state-of-the-art deep learning models on Apache Spark.What you will learnSet up a fully functional Spark environmentUnderstand practical machine learning and deep learning conceptsEmploy built-in machine learning libraries within SparkDiscover libraries that are compatible with TensorFlow and KerasExplore NLP models such as word2vec and TF-IDF on SparkOrganize DataFrames for deep learning evaluationApply testing and training modeling to ensure accuracyAccess readily available code that can be reusedWho this book is forIf you’re looking for a practical resource for implementing efficiently distributed deep learning models with Apache Spark, then this book is for you. Knowledge of core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the most out of this book. Some knowledge of Python programming will also be useful.