Free PDF Deep Learning with Hadoop
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Key FeaturesGet to grips with the deep learning concepts and set up Hadoop to put them to useImplement and parallelize deep learning models on Hadoop's YARN frameworkA comprehensive tutorial to distributed deep learning with HadoopBook DescriptionThis book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop for optimal performance.Starting with understanding what deep learning is, and what the various models associated with deep neural networks are, this book will then show you how to set up the Hadoop environment for deep learning. In this book, you will also learn how to overcome the challenges that you face while implementing distributed deep learning with large-scale unstructured datasets. The book will also show you how you can implement and parallelize the widely used deep learning models such as Deep Belief Networks, Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann Machines and autoencoder using the popular deep learning library deeplearning4j.Get in-depth mathematical explanations and visual representations to help you understand the design and implementations of Recurrent Neural network and Denoising AutoEncoders with deeplearning4j. To give you a more practical perspective, the book will also teach you the implementation of large-scale video processing, image processing and natural language processing on Hadoop.By the end of this book, you will know how to deploy various deep neural networks in distributed systems using Hadoop.What you will learnExplore Deep Learning and various models associated with itUnderstand the challenges of implementing distributed deep learning with Hadoop and how to overcome itImplement Convolutional Neural Network (CNN) with deeplearning4jDelve into the implementation of Restricted Boltzmann Machines (RBM)Understand the mathematical explanation for implementing Recurrent Neural Networks (RNN)Get hands on practice of deep learning and their implementation with Hadoop.About the AuthorDipayan Dev has completed his M.Tech from National Institute of Technology, Silchar with a first class first and is currently working as a software professional in Bengaluru, India. He has extensive knowledge and experience in non-relational database technologies, having primarily worked with large-scale data over the last few years. His core expertise lies in Hadoop Framework. During his postgraduation, Dipayan had built an infinite scalable framework for Hadoop, called Dr. Hadoop, which got published in top-tier SCI-E indexed journal of Springer (http://link.springer.com/article/10.1631/FITEE.1500015). Dr. Hadoop has recently been cited by Goo Wikipedia in their Apache Hadoop article. Apart from that, he registers interest in a wide range of distributed system technologies, such as Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and other NoSQL databases. Dipayan has also authored various research papers and book chapters, which are published by IEEE and top-tier Springer Journals. To know more about him, you can also visit his LinkedIn profile https://www.linkedin.com/in/dipayandev.Table of ContentsIntroduction to Deep LearningDistributed Deep Learning for Large-Scale DataConvolutional Neural NetworkRecurrent Neural NetworkRestricted Boltzmann MachinesAutoencodersMiscellaneous Deep Learning Operations using HadoopReferences The Hadoop Ecosystem Table Fork Me on GitHub The Hadoop Ecosystem Table This page is a summary to keep the track of Hadoop related projects focused on FLOSS environment What is deep learning? SAS Deep learning is a type of machine learning that uses deep neural networks to train a computer to perform human-like tasks like recognizing speech or images Deep Learning: Intelligence from Big Data - YouTube Deep Learning: Intelligence from Big Data Tue Sep 16 2014 6:00 pm - 8:30 pm Stanford Graduate School of Business Knight Management Center Cemex Auditorium Big Data Hadoop Online Training Hadoop Certification This Hadoop training is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop ecosystem and best practices about Review: The best frameworks for machine learning and deep Review: The best frameworks for machine learning and deep learning TensorFlow Spark MLlib Scikit-learn MXNet Microsoft Cognitive Toolkit and Caffe do the math Machine Learning Prague conference on machine learning Machine learning in malware detection: a paradigm of zero FPR (1) In malware detection an extremely low false positive rate is one of the most important targets What is Apache Hadoop? - Hortonworks Apache Hadoop is an open source software platform for distributed storage and distributed processing of very large data sets on computer clusters Apache Hadoop Wiki - FrontPage - General Wiki Apache Hadoop Apache Hadoop is a framework for running applications on large cluster built of commodity hardware The Hadoop framework transparently provides Hadoop Cloudera Hortonworks MapR Certification AWS Hadoop Cloudera Hortonworks CCD-410CCA175CCA159CCP:DE575 CCA-500 MCHBD (MapR HBase) CCSHB HBase AWS Certification Cloudera dump CCA175 DE575 CCA -500 CCA Deeplearning4j: Open-source Distributed Deep Learning for Open-Source Deep-Learning Software for Java and Scala on Hadoop and Spark
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