{"product_id":"deep-learning-a-practitioners-approach-paperback","title":"Deep Learning: A Practitioner's Approach - Paperback","description":"\u003cp\u003eby \u003cb\u003eJosh Patterson\u003c\/b\u003e (Author), \u003cb\u003eAdam Gibson\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAlthough interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learningâ especially deep neural networksâ make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. \u003c\/p\u003e\u003cp\u003e Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, youâ ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eDive into machine learning concepts in general, as well as deep learning in particular \u003c\/li\u003e\n\u003cli\u003eUnderstand how deep networks evolved from neural network fundamentals \u003c\/li\u003e\n\u003cli\u003eExplore the major deep network architectures, including Convolutional and Recurrent \u003c\/li\u003e\n\u003cli\u003eLearn how to map specific deep networks to the right problem \u003c\/li\u003e\n\u003cli\u003eWalk through the fundamentals of tuning general neural networks and specific deep network architectures \u003c\/li\u003e\n\u003cli\u003eUse vectorization techniques for different data types with DataVec, DL4Jâ s workflow tool \u003c\/li\u003e\n\u003cli\u003eLearn how to use DL4J natively on Spark and Hadoop \u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eJosh Patterson is CEO of Patterson Consulting, a solution integrator at the intersection of big data and applied machine learning. In this role, he brings his unique perspective blending a decade of big data experience and wide-ranging deep learning experience to Fortune 500 projects. At the Tennessee Valley Authority (TVA), Josh drove the integration of Apache Hadoop for large-scale data storage and processing of smart grid phasor measurement unit (PMU) data. Post-TVA, Josh was a principal solutions architect for a young Hadoop startup named Cloudera (CLDR), as employee 34. After leaving Cloudera, Josh co-founded the Deeplearning4j project and co-wrote Deep Learning: A Practitioner's Approach (O'Reilly Media). Josh was also the VP of Field Engineering for Skymind.\u003c\/p\u003e\u003cp\u003eAdam Gibson is a deep learning specialist based in San Francisco who works with Fortune 500 companies, hedge funds, PR firms and startup accelerators to create their machine -learning projects. Adam has a strong track record helping companies handle and interpret big real-time data. Adam has been a computer nerd since he was 13, and actively contributes to the open source community through deeplearning4j.org.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 530\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1 x 9.1 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 12, 2017\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42693357469759,"sku":"9781491914250","price":71.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/b71d5cf45dd8beca73e3e22254296d84.webp?v=1764998666","url":"https:\/\/dhlswag.com\/products\/deep-learning-a-practitioners-approach-paperback","provider":"BBB","version":"1.0","type":"link"}