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Машинное обучение (Machine Learning)

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Packt Publishing Ltd., 2020. — 530 p. — ISBN: 978-1-78995-533-0. Code files only! Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasets C++ can make your machine learning models run faster and more efficiently. This handy guide...
  • №1
  • 1,11 МБ
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Packt, 2020. — 246 p. — ISBN: 9781838646486. Code files only! Build secure private blockchain networks to handle mission-critical security challenges such as denial-of-service attacks, user wallets, and pool mining attacks Key Features Explore blockchain concepts such as cryptography, consensus algorithms, and security assumptions Architect network security for mission-critical...
  • №2
  • 39,58 МБ
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Apress, 2017. - 358p. - ISBN: 978-1484228654 Code files only! Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning...
  • №3
  • 20,22 МБ
  • добавлен
  • описание отредактировано
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