Computer Vision Projects with Pytorch: Design and Develop Production-Grade Models (Paperback)
暫譯: 使用 Pytorch 的電腦視覺專案：設計與開發生產級模型 (平裝本)

Kulkarni, Akshay, Shivananda, Adarsha, Sharma, Nitin Ranjan

Computer Vision Projects with Pytorch: Design and Develop Production-Grade Models (Paperback)
  • 出版商: Apress
  • 出版日期: 2022-07-19
  • 售價: $1,925
  • 貴賓價: 9.5 折 $1,829
  • 語言: 英文
  • 頁數: 330
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484282728
  • ISBN-13: 9781484282724
  • 相關分類: DeepLearning、Computer Vision

    • 立即出貨 (庫存=1)

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商品描述

Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch.
The book begins with the fundamentals of computer vision: convolutional neural nets, RESNET, YOLO, data augmentation, and other regularization techniques used in the industry. And then it gives you a quick overview of the PyTorch libraries used in the book. After that, it takes you through the implementation of image classification problems, object detection techniques, and transfer learning while training and running inference. The book covers image segmentation and an anomaly detection model. And it discusses the fundamentals of video processing for computer vision tasks putting images into videos. The book concludes with an explanation of the complete model building process for deep learning frameworks using optimized techniques with highlights on model AI explainability.
After reading this book, you will be able to build your own computer vision projects using transfer learning and PyTorch.

What You Will Learn

- Solve problems in computer vision with PyTorch.
- Implement transfer learning and perform image classification, object detection, image segmentation, and other computer vision applications
- Design and develop production-grade computer vision projects for real-world industry problems
- Interpret computer vision models and solve business problems


Who This Book Is For
Data scientists and machine learning engineers interested in building computer vision projects and solving business problems

商品描述(中文翻譯)

設計和開發端到端的生產級計算機視覺專案，以解決現實世界中的行業問題。本書討論了計算機視覺算法及其在 PyTorch 中的應用。
本書首先介紹計算機視覺的基本原理：卷積神經網絡（convolutional neural nets）、RESNET、YOLO、數據增強（data augmentation）以及其他在行業中使用的正則化技術。接著，簡要概述了本書中使用的 PyTorch 函式庫。之後，將帶您了解圖像分類問題的實現、物體檢測技術和轉移學習（transfer learning），同時進行訓練和推理。書中涵蓋了圖像分割和異常檢測模型，並討論了計算機視覺任務中的視頻處理基礎，將圖像轉換為視頻。最後，本書解釋了使用優化技術的深度學習框架的完整模型構建過程，並強調模型的 AI 可解釋性。
閱讀完本書後，您將能夠使用轉移學習和 PyTorch 構建自己的計算機視覺專案。

您將學到什麼
- 使用 PyTorch 解決計算機視覺中的問題。
- 實現轉移學習並執行圖像分類、物體檢測、圖像分割及其他計算機視覺應用。
- 設計和開發針對現實世界行業問題的生產級計算機視覺專案。
- 解釋計算機視覺模型並解決商業問題。

本書適合誰
對構建計算機視覺專案和解決商業問題感興趣的數據科學家和機器學習工程師。

作者簡介

Akshay R Kulkarni is an AI and machine learning (ML) evangelist and a thought leader. He has consulted for Fortune 500 and global enterprises to drive AI and data science-led strategic transformations. He is currently the manager of data science & AI at Publicis Sapien. He is a Google developer and author of the book Natural Language Processing Recipes (Apress). He is a regular speaker at major AI and data science conferences (including Strata, O’Reilly AI Conf, and GIDS). Akshay is a visiting faculty member for some of the top graduate institutes in India. In 2019, he was featured as one of the top 40 under 40 Data Scientists in India. In his spare time, he enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.

Adarsha Shivananda is a senior data scientist on Indegene's product and technology team where he works on building machine learning and artificial intelligence (AI) capabilities for pharma products. He aims to build a pool of exceptional data scientists within and outside of the organization to solve problems through training programs, and always wants to stay ahead of the curve. Previously, he worked with Tredence Analytics and IQVIA. He has worked extensively in the pharma, healthcare, retail, and marketing domains. He lives in Bangalore and loves to read and teach data science.

Nitin Ranjan Sharma is a manager at Novartis, involved in leading a team to develop products using multi-modal techniques. He has been a consultant developing solutions for Fortune 500 companies, involved in solving complex business problems using machine learning and deep learning frameworks. His major focus area and core expertise are computer vision and solving some of the challenging business problems dealing with images and video data. Before Novartis, he was part of the data science team at Publicis Sapient, EY, and TekSystems Global Services. He is a regular speaker at data science communities and meet-ups and also an open-source contributor. He has also been training and mentoring data science enthusiasts.

作者簡介(中文翻譯)

Akshay R Kulkarni 是一位人工智慧 (AI) 和機器學習 (ML) 的推廣者及思想領袖。他曾為《財富》500 強企業及全球企業提供諮詢，推動以 AI 和數據科學為主導的戰略轉型。目前，他是 Publicis Sapient 的數據科學與 AI 經理。他是 Google 開發者，也是書籍《自然語言處理食譜》（Apress）的作者。他經常在主要的 AI 和數據科學會議上發言（包括 Strata、O'Reilly AI Conf 和 GIDS）。Akshay 是印度一些頂尖研究所的客座教授。2019 年，他被評選為印度 40 位 40 歲以下的頂尖數據科學家之一。在空閒時間，他喜歡閱讀、寫作、編程，並幫助有志於成為數據科學家的朋友。他與家人居住在班加羅爾。

Adarsha Shivananda 是 Indegene 產品與技術團隊的高級數據科學家，負責為製藥產品建立機器學習和人工智慧 (AI) 能力。他的目標是建立一個卓越的數據科學家團隊，無論是在組織內部還是外部，通過培訓計劃解決問題，並始終希望走在潮流之前。之前，他曾在 Tredence Analytics 和 IQVIA 工作。他在製藥、醫療保健、零售和行銷領域有廣泛的工作經驗。他居住在班加羅爾，喜歡閱讀和教授數據科學。

Nitin Ranjan Sharma 是 Novartis 的經理，負責領導團隊使用多模態技術開發產品。他曾擔任顧問，為《財富》500 強公司開發解決方案，專注於使用機器學習和深度學習框架解決複雜的商業問題。他的主要專注領域和核心專業是計算機視覺，並解決一些與影像和視頻數據相關的挑戰性商業問題。在加入 Novartis 之前，他曾是 Publicis Sapient、EY 和 TekSystems Global Services 的數據科學團隊成員。他經常在數據科學社群和聚會上發言，並且也是開源貢獻者。他還一直在培訓和指導數據科學愛好者。

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