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    Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x Saif Ahmed, Quan Hua, Shams Ul Azeem

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x Saif Ahmed, Quan Hua, Shams Ul Azeem - okladka książki

    Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x Saif Ahmed, Quan Hua, Shams Ul Azeem - okladka książki

    Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x Saif Ahmed, Quan Hua, Shams Ul Azeem - audiobook MP3

    Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x Saif Ahmed, Quan Hua, Shams Ul Azeem - audiobook CD

    Autorzy:
    Saif Ahmed, Quan Hua, Shams Ul Azeem
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    304
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x.

    Firstly, you’ll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data ?ow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You’ll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you’ll implement a complete real-life production system from training to serving a deep learning model. As you advance you’ll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you’ll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.

    By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.

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    O autorach książki

    Saif Ahmed is an accomplished quantitative analyst and data scientist with 15 years of industry experience. His career started in management consulting at Accenture and lead him to quantitative and senior management roles at Goldman Sachs and AIG Investments. Most recently, he co-founded and runs a start-up focused on applying Deep Learning to automating medical imaging. He obtained his bachelor's degree in computer science from Cornell University and is currently pursuing a graduate degree in data science at U.C. Berkeley.
    Quan Hua is a Computer Vision and Machine Learning Engineer at BodiData, a data platform for body measurements, where he focuses on developing computer vision and machine learning applications for a handheld technology capable of acquiring a body avatar while a person is fully clothed. He earned a bachelor of science degree from the University of Science, Vietnam, specializing in Computer Vision. He has been working in the field of computer vision and machine learning for about 3 years at start-ups. Quan has been writing for Packt since 2015 for a Computer Vision book, OpenCV 3 Blueprints.
    Shams Ul Azeem is an undergraduate in electrical engineering from NUST Islamabad, Pakistan. He has a great interest in the computer science field, and he started his journey with Android development. Now, hes pursuing his career in Machine Learning, particularly in deep learning, by doing medical-related freelancing projects with different companies. He was also a member of the RISE lab, NUST, and he has a publication credit at the IEEE International Conference, ROBIO as a co-author of Designing of motions for humanoid goalkeeper robots.

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