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Fundamentals of Deep Learning and Computer Vision Nikhil Singh, Paras Ahuja

(ebook) (audiobook) (audiobook) Książka w języku 1
Fundamentals of Deep Learning and Computer Vision Nikhil Singh, Paras Ahuja - okladka książki

Fundamentals of Deep Learning and Computer Vision Nikhil Singh, Paras Ahuja - okladka książki

Fundamentals of Deep Learning and Computer Vision Nikhil Singh, Paras Ahuja - audiobook MP3

Fundamentals of Deep Learning and Computer Vision Nikhil Singh, Paras Ahuja - audiobook CD

Autorzy:
Nikhil Singh, Paras Ahuja
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
181
Dostępne formaty:
     ePub
     Mobi
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Master Computer Vision concepts using Deep Learning with easy-to-follow steps

Key Features
  • Setting up the Python and TensorFlow environment
  • Learn core Tensorflow concepts with the latest TF version 2.0
  • Learn Deep Learning for computer vision applications
  • Understand different computer vision concepts and use-cases
  • Understand different state-of-the-art CNN architectures
  • Build deep neural networks with transfer Learning using features from pre-trained CNN models
  • Apply computer vision concepts with easy-to-follow code in Jupyter Notebook

  • Description
    This book starts with setting up a Python virtual environment with the deep learning framework TensorFlow and then introduces the fundamental concepts of TensorFlow. Before moving on to Computer Vision, you will learn about neural networks and related aspects such as loss functions, gradient descent optimization, activation functions and how backpropagation works for training multi-layer perceptrons.
    To understand how the Convolutional Neural Network (CNN) is used for computer vision problems, you need to learn about the basic convolution operation. You will learn how CNN is different from a multi-layer perceptron along with a thorough discussion on the different building blocks of the CNN architecture such as kernel size, stride, padding, and pooling and finally learn how to build a small CNN model.
    The book concludes with a chapter on sequential models where you will learn about RNN, GRU, and LSTMs and their architectures and understand their applications in machine translation, image/video captioning and video classification.

    O autorze książki

    Nikhil Singh is a computer vision and natural language processing engineer who likes to apply his knowledge of machine learning and deep learning to solve intriguing problems. He currently works as a data scientist for Alixpartners, London. After getting satisfactory results, he believes his work will help Alixpartners to achieve more excellence in their field. He is also the prime author of the book "Video Analytics using TensorFlow" for Apress Publication.

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