Computer And Machine Vision: Theory

Mastering Computer Vision-Theory & Projects in Python  eBooks & eLearning

Posted by lucky_aut at Feb. 2, 2021
Mastering Computer Vision-Theory & Projects in Python

Mastering Computer Vision-Theory & Projects in Python
Duration: 26h 57m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 10.7 GB
Genre: eLearning | Language: English

Computer Vision-Become an ace of Computer Vision, Detect Shapes and Create Apps using Python, OpenCV, TensorFlow, etc.
Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools

Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools, techniques and algorithms, 4th Edition by Joseph Howse, Joe Minichino
English | August 11, 2025 | ISBN: 1803230223 | 282 pages | PDF | 44 Mb
Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools

Learning OpenCV 5 Computer Vision with Python: Tackle computer vision and machine learning with the newest tools, techniques and algorithms, 4th Edition by Joseph Howse, Joe Minichino
English | August 11, 2025 | ISBN: 1803230223 | 282 pages | PDF | 44 Mb

Master Computer Vision™ OpenCV3 in Python and Machine Learning  eBooks & eLearning

Posted by IrGens at Oct. 26, 2018
Master Computer Vision™ OpenCV3 in Python and Machine Learning

Master Computer Vision™ OpenCV3 in Python and Machine Learning
.MP4, AVC, 200 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 6h 14m | 1.42 GB
Instructor: Rajeev Ratan

Artificial Intelligence and Machine Learning: Complete Guide  eBooks & eLearning

Posted by Sigha at March 21, 2025
Artificial Intelligence and Machine Learning: Complete Guide

Artificial Intelligence and Machine Learning: Complete Guide
2025-02-06
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 8.68 GB | Duration: 22h 19m

Do you want to study AI and don't know where to start? You will learn everything you need to know in theory and practice

Artificial Intelligence and Machine Learning: Complete Guide  eBooks & eLearning

Posted by IrGens at Sept. 17, 2023
Artificial Intelligence and Machine Learning: Complete Guide

Artificial Intelligence and Machine Learning: Complete Guide
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 22h 12m | 7.98 GB
Instructor: Jones Granatyr

Learn OpenCV Python 2022 | Computer Vision Course  eBooks & eLearning

Posted by lucky_aut at Feb. 25, 2022
Learn OpenCV Python 2022 | Computer Vision Course

Learn OpenCV Python 2022 | Computer Vision Course
Duration: 5h | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.29 GB
Genre: eLearning | Language: English

OpenCV Python from Scratch

Artificial Intelligence and Machine Learning: Complete Guide  eBooks & eLearning

Posted by Sigha at March 21, 2025
Artificial Intelligence and Machine Learning: Complete Guide

Artificial Intelligence and Machine Learning: Complete Guide
2025-02-06
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 8.68 GB | Duration: 22h 19m

Do you want to study AI and don't know where to start? You will learn everything you need to know in theory and practice

Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Repost)  eBooks & eLearning

Posted by step778 at Feb. 21, 2017
Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Repost)

Gregory Shakhnarovich, Trevor Darrell, Piotr Indyk, "Nearest-Neighbor Methods in Learning and Vision: Theory and Practice"
2006 | pages: 263 | ISBN: 026219547X | PDF | 28,4 mb

Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (repost)  eBooks & eLearning

Posted by interes at June 23, 2013
Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (repost)

Nearest-Neighbor Methods in Learning and Vision: Theory and Practice by Gregory Shakhnarovich
English | (March 24, 2006) | ISBN: 026219547X | Pages: 280 | PDF | 7,18 MB

Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances in computational geometry and machine learning, however, may alleviate the problems in using these methods on large data sets.