Day 3 - Convolutional Neural Network (CNN) & Feature Extractor | Computer Vision for Developers
In this Computer Vision tutorial, we’ll explore Convolutional Neural Networks (CNNs) from scratch and understand how CNNs act as powerful feature extractors in Computer Vision tasks. Whether you're working on image classification, object detection, or feature engineering — this session will boost your foundation and practical skills.
📌Class Materials: https://github.com/entbappy/Computer-Vision-for-Developers
👉 Don’t forget to subscribe to the playlist to get all the updates on computer vision!
#OpenCV #ImageProcessing #ComputerVision #Python #MachineLearning #ArtificialIntelligence #DeepLearning #AIDeveloper #OpenCVPython #ComputerVisionProjects #AIProjects #MLProjects #Coding #PythonTutorial #InceptionBD
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► MLOps Production Ready Machine Learning Project: https://youtube.com/playlist?list=PLkz_y24mlSJZvJOj1UXiJPVRQrNFdNEXX&si=yxL3EpwDcOslx3du
► End To End Data Science Projects Implementation: https://youtube.com/playlist?list=PLkz_y24mlSJaGcOXgJSuMM62sFha4fank&si=L0O96gFeduHCEVdi
► MLflow For Data Science | MLOps: https://youtube.com/playlist?list=PLkz_y24mlSJZrqiZ4_cLUiP0CBN5wFmTb&si=mOOoyy6gcNmG3IqS
► The Complete Self Driving Car Course: https://youtube.com/playlist?list=PLkz_y24mlSJawbZz-fJrrxZi0QNmJ5aP6&si=iC2PZhLG5Q5J3tF6
► Object Detection Using YOLO v6: https://youtube.com/playlist?list=PLkz_y24mlSJY3H0WZGY2XKvuFdvkJS9oM
► Object Detection Using YOLO v7: https://youtube.com/playlist?list=PLkz_y24mlSJagh6O2MIrgI-Ki-t1rhjLI
► Sign Language Detection Using YOLO v5: https://youtube.com/playlist?list=PLkz_y24mlSJYWpwFbU8fyaBSwihoVHiJz
►ONNX (Open Neural Network Exchange): https://youtube.com/playlist?list=PLkz_y24mlSJZJx9sQJCyFZt50S4ji1PeR
😀Please donate if you want to support the channel through Buy me a coffee: https://www.buymeacoffee.com/dswithbappy
This channel focuses on providing content on Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, etc. in English.
My mission is to provide inspiration, motivation & good quality education to students for learning and human development, and to become an expert in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, and so on.
#dswithbappy aims to provide unique & high-quality free education.
I believe that high-quality education is not just for the privileged few. It is the right of everyone who seeks it. My aim is to bring quality education to every single student. All I need from you is intent, and a ray of passion to learn.
Thanks!
#dswithbappy
Connect with me here:
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Github: https://github.com/entbappy
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Видео Day 3 - Convolutional Neural Network (CNN) & Feature Extractor | Computer Vision for Developers канала DSwithBappy
📌Class Materials: https://github.com/entbappy/Computer-Vision-for-Developers
👉 Don’t forget to subscribe to the playlist to get all the updates on computer vision!
#OpenCV #ImageProcessing #ComputerVision #Python #MachineLearning #ArtificialIntelligence #DeepLearning #AIDeveloper #OpenCVPython #ComputerVisionProjects #AIProjects #MLProjects #Coding #PythonTutorial #InceptionBD
Check out my other playlists:
► MLOps Production Ready Machine Learning Project: https://youtube.com/playlist?list=PLkz_y24mlSJZvJOj1UXiJPVRQrNFdNEXX&si=yxL3EpwDcOslx3du
► End To End Data Science Projects Implementation: https://youtube.com/playlist?list=PLkz_y24mlSJaGcOXgJSuMM62sFha4fank&si=L0O96gFeduHCEVdi
► MLflow For Data Science | MLOps: https://youtube.com/playlist?list=PLkz_y24mlSJZrqiZ4_cLUiP0CBN5wFmTb&si=mOOoyy6gcNmG3IqS
► The Complete Self Driving Car Course: https://youtube.com/playlist?list=PLkz_y24mlSJawbZz-fJrrxZi0QNmJ5aP6&si=iC2PZhLG5Q5J3tF6
► Object Detection Using YOLO v6: https://youtube.com/playlist?list=PLkz_y24mlSJY3H0WZGY2XKvuFdvkJS9oM
► Object Detection Using YOLO v7: https://youtube.com/playlist?list=PLkz_y24mlSJagh6O2MIrgI-Ki-t1rhjLI
► Sign Language Detection Using YOLO v5: https://youtube.com/playlist?list=PLkz_y24mlSJYWpwFbU8fyaBSwihoVHiJz
►ONNX (Open Neural Network Exchange): https://youtube.com/playlist?list=PLkz_y24mlSJZJx9sQJCyFZt50S4ji1PeR
😀Please donate if you want to support the channel through Buy me a coffee: https://www.buymeacoffee.com/dswithbappy
This channel focuses on providing content on Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, etc. in English.
My mission is to provide inspiration, motivation & good quality education to students for learning and human development, and to become an expert in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, and so on.
#dswithbappy aims to provide unique & high-quality free education.
I believe that high-quality education is not just for the privileged few. It is the right of everyone who seeks it. My aim is to bring quality education to every single student. All I need from you is intent, and a ray of passion to learn.
Thanks!
#dswithbappy
Connect with me here:
Twitter: https://twitter.com/bappy913873
Facebook: https://www.facebook.com/groups/dswithbappy
instagram: https://www.instagram.com/entbappy/
linkedin : https://www.linkedin.com/in/boktiarahmed73/
Github: https://github.com/entbappy
🙏🙏🙏🙏🙏🙏🙏🙏
YOU JUST NEED TO DO
3 THINGS to support my channel
LIKE
SHARE
&
SUBSCRIBE
TO MY YOUTUBE CHANNEL
Видео Day 3 - Convolutional Neural Network (CNN) & Feature Extractor | Computer Vision for Developers канала DSwithBappy
convolutional neural network cnn deep learning cnn feature extraction cnn tutorial python cnn keras tutorial cnn pytorch tutorial computer vision cnn deep learning image classification cnn transfer learning feature extraction deep learning image processing cnn deep learning tutorial keras cnn model pytorch cnn example how cnn works cnn architecture explained cnn filters feature maps
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4 мая 2025 г. 10:41:48
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