Computer Vision Projects with PyTorch - Akshay Kulkarni - E-Book
SONDERANGEBOT

Computer Vision Projects with PyTorch E-Book

Akshay Kulkarni

0,0
62,99 €
Niedrigster Preis in 30 Tagen: 46,99 €

-100%
Sammeln Sie Punkte in unserem Gutscheinprogramm und kaufen Sie E-Books und Hörbücher mit bis zu 100% Rabatt.

Mehr erfahren.
Beschreibung

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

Das E-Book können Sie in einer beliebigen App lesen, die das folgende Format unterstützt:

PDF

Veröffentlichungsjahr: 2022

Bewertungen
0,0
0
0
0
0
0
Mehr Informationen
Mehr Informationen
Legimi prüft nicht, ob Rezensionen von Nutzern stammen, die den betreffenden Titel tatsächlich gekauft oder gelesen/gehört haben. Wir entfernen aber gefälschte Rezensionen.