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Download the fantastic book titled Modern Computer Vision with PyTorch written by V Kishore Ayyadevara, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Modern Computer Vision with PyTorch", which was released on 27 November 2020. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Modern Computer Vision with PyTorch by V Kishore Ayyadevara PDF

Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions Key FeaturesImplement solutions to 50 real-world computer vision applications using PyTorchUnderstand the theory and working mechanisms of neural network architectures and their implementationDiscover best practices using a custom library created especially for this bookBook Description Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. This book takes a hands-on approach to help you to solve over 50 CV problems using PyTorch1.x on real-world datasets. You’ll start by building a neural network (NN) from scratch using NumPy and PyTorch and discover best practices for tweaking its hyperparameters. You’ll then perform image classification using convolutional neural networks and transfer learning and understand how they work. As you progress, you’ll implement multiple use cases of 2D and 3D multi-object detection, segmentation, human-pose-estimation by learning about the R-CNN family, SSD, YOLO, U-Net architectures, and the Detectron2 platform. The book will also guide you in performing facial expression swapping, generating new faces, and manipulating facial expressions as you explore autoencoders and modern generative adversarial networks. You’ll learn how to combine CV with NLP techniques, such as LSTM and transformer, and RL techniques, such as Deep Q-learning, to implement OCR, image captioning, object detection, and a self-driving car agent. Finally, you'll move your NN model to production on the AWS Cloud. By the end of this book, you’ll be able to leverage modern NN architectures to solve over 50 real-world CV problems confidently. What you will learnTrain a NN from scratch with NumPy and PyTorchImplement 2D and 3D multi-object detection and segmentationGenerate digits and DeepFakes with autoencoders and advanced GANsManipulate images using CycleGAN, Pix2PixGAN, StyleGAN2, and SRGANCombine CV with NLP to perform OCR, image captioning, and object detectionCombine CV with reinforcement learning to build agents that play pong and self-drive a carDeploy a deep learning model on the AWS server using FastAPI and DockerImplement over 35 NN architectures and common OpenCV utilitiesWho this book is for This book is for beginners to PyTorch and intermediate-level machine learning practitioners who are looking to get well-versed with computer vision techniques using deep learning and PyTorch. If you are just getting started with neural networks, you’ll find the use cases accompanied by notebooks in GitHub present in this book useful. Basic knowledge of the Python programming language and machine learning is all you need to get started with this book.


Detail About Modern Computer Vision with PyTorch PDF

  • Author : V Kishore Ayyadevara
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 805 pages
  • ISBN : 1839216530
  • PDF File Size : 15,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch
  • Publisher : Packt Publishing Ltd
  • File Size : 42,8 Mb
  • Release Date : 27 November 2020
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Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions Key FeaturesImplement solutions to 50 real-world computer vision

PyTorch Deep Learning Hands-On

PyTorch Deep Learning Hands-On
  • Publisher : Packt Publishing Ltd
  • File Size : 23,5 Mb
  • Release Date : 30 April 2019
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Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch Key FeaturesInternals and principles of PyTorchImplement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning,

PyTorch Computer Vision Cookbook

PyTorch Computer Vision Cookbook
  • Publisher : Unknown Publisher
  • File Size : 22,9 Mb
  • Release Date : 20 March 2020
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Discover powerful ways to use deep learning algorithms and solve real-world computer vision problems using Python Key Features Solve the trickiest of problems in computer vision by combining the power

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch
  • Publisher : Packt Publishing Ltd
  • File Size : 26,7 Mb
  • Release Date : 10 June 2024
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The definitive computer vision book is back, featuring the latest neural network architectures and an exploration of foundation and diffusion models Purchase of the print or Kindle book includes a

PyTorch Deep Learning Hands-On

PyTorch Deep Learning Hands-On
  • Publisher : Unknown Publisher
  • File Size : 21,6 Mb
  • Release Date : 26 April 2019
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All the key deep learning methods built step-by-step in PyTorch Key Features Understand the internals and principles of PyTorch Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement

Deep Learning with PyTorch

Deep Learning with PyTorch
  • Publisher : Simon and Schuster
  • File Size : 31,8 Mb
  • Release Date : 01 July 2020
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“We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of

Hands-On Generative Adversarial Networks with PyTorch 1.x

Hands-On Generative Adversarial Networks with PyTorch 1.x
  • Publisher : Packt Publishing Ltd
  • File Size : 20,8 Mb
  • Release Date : 12 December 2019
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Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models Key FeaturesImplement GAN architectures to generate images, text, audio, 3D models, and moreUnderstand how

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch
  • Publisher : O'Reilly Media
  • File Size : 53,6 Mb
  • Release Date : 29 June 2020
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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results

Hands-On Computer Vision with TensorFlow 2

Hands-On Computer Vision with TensorFlow 2
  • Publisher : Packt Publishing Ltd
  • File Size : 34,7 Mb
  • Release Date : 30 May 2019
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A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural

Practical Machine Learning for Computer Vision

Practical Machine Learning for Computer Vision
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 33,9 Mb
  • Release Date : 21 July 2021
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This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image