Computer vision from image processing to generative AI and vision transformers.
In this 34-hour course, learners will explore computer vision from image processing fundamentals to advanced generative AI and Vision Transformers, gaining hands-on experience with CNNs, GANs, object detection, segmentation, and embedding-based image search for real-world AI applications. What I wil...
Gespeichert in:
- 1. Verfasser:
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- Format:
- Elektronisch Film
- Sprache:
- Englisch
- Veröffentlicht:
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[Birmingham, United Kingdom] :
Packt Publishing,
2026.
- Ausgabe:
- [First edition].
- Zusammenfassung:
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In this 34-hour course, learners will explore computer vision from image processing fundamentals to advanced generative AI and Vision Transformers, gaining hands-on experience with CNNs, GANs, object detection, segmentation, and embedding-based image search for real-world AI applications. What I will be able to do after this course Apply computer vision and deep learning techniques to real-world projects Build and optimize convolutional neural networks for image tasks Implement generative AI models including GANs and autoencoders Leverage Vision Transformers for advanced visual recognition Design pipelines for object detection, segmentation, and image retrieval Course Instructor(s) Vinit Kumar Singh is an AI Consultant and Educator with 18+ years in Data Science, LLM Fine-Tuning, Voice AI, and Computer Vision. He has IIT Bombay and Stanford certifications, leads AI initiatives at Sony India Software Centre, and is a top 3% global Udemy creator trusted by enterprises worldwide. Who is it for? This course is designed for AI developers, computer vision engineers, and data scientists with prior Python experience. Ideal for those with foundational knowledge in machine learning and linear algebra, it equips learners with practical skills to implement CNNs, GANs, Vision Transformers, object detection, segmentation, and embedding-based search in real-world AI projects.
- Umfang:
- 1 online resource (1 video file (34 hr., 5 min.)) : sound, color.
- ISBN:
- 9781808086335
- Schlagworte:
- Links: