Deep Learning: A Practitioner's Approach

Josh Patterson · Adam Gibson

Jul 2017 · "O'Reilly Media, Inc."

Kitabu pepe

532

Kurasa

Kimetimiza masharti

Ukadiriaji na maoni hayajahakikishwa Pata Maelezo Zaidi

Kuhusu kitabu pepe hiki

Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—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.

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, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.

Dive into machine learning concepts in general, as well as deep learning in particular
Understand how deep networks evolved from neural network fundamentals
Explore the major deep network architectures, including Convolutional and Recurrent
Learn how to map specific deep networks to the right problem
Walk through the fundamentals of tuning general neural networks and specific deep network architectures
Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool
Learn how to use DL4J natively on Spark and Hadoop

Kuhusu mwandishi

Josh 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.

Adam 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 realtime data. Adam has been a computer nerd since he was 13, and actively contributes to the open-source community through deeplearning4j.org.

Kadiria kitabu pepe hiki

Tupe maoni yako.

Kusoma maelezo

Simu mahiri na kompyuta vibao

Sakinisha programu ya Vitabu vya Google Play kwa ajili ya Android na iPad au iPhone. Itasawazishwa kiotomatiki kwenye akaunti yako na kukuruhusu usome vitabu mtandaoni au nje ya mtandao popote ulipo.

Kompyuta za kupakata na kompyuta

Unaweza kusikiliza vitabu vilivyonunuliwa kwenye Google Play wakati unatumia kivinjari cha kompyuta yako.

Visomaji pepe na vifaa vingine

Ili usome kwenye vifaa vya wino pepe kama vile visomaji vya vitabu pepe vya Kobo, utahitaji kupakua faili kisha ulihamishie kwenye kifaa chako. Fuatilia maagizo ya kina ya Kituo cha Usaidizi ili uhamishe faili kwenye visomaji vya vitabu pepe vinavyotumika.

Ripoti maudhui yanayokiuka sera