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Pledge for Add-ons without a reward on Kickstarter

OpenCV University
112K subscribers
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411 views 3 years ago
Check out our course on Kickstarter: https://bit.ly/3u4jPbE 37% discount [ Valid till June 19, 2021 ] This course is designed to build a strong foundation in Computer Vision. You will get a solid understanding of all the tools in OpenCV for Image Processing, Computer Vision, Video Processing and the basics of AI. you will build systems or applications using the techniques learned in the first course as well as some new ones that we cover as we go along. We also cover a substantial amount of Machine Learning and the basics of Deep Learning in this course. We will also build interesting Web Applications as part of the course curriculum. we will start with a theoretical understanding of simple neural nets and gradually move to Deep Neural Nets and Convolutional Neural Networks. Not only will we go over Deep Net architectures used for solving various computer vision problems, we will also go over practical considerations needed to successfully train Deep Neural Networks. These include how to prepare datasets, how to perform sanity checks before embarking on training that can take hours, how to use visualization tools to debug the training process, what workflows to use when the results are not satisfactory, and finally how to deploy your network on the cloud. ...more
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Pledge for Add-ons without a reward on Kickstarter
5Likes
411Views
2021Jun 1
Check out our course on Kickstarter: https://bit.ly/3u4jPbE 37% discount [ Valid till June 19, 2021 ] This course is designed to build a strong foundation in Computer Vision. You will get a solid understanding of all the tools in OpenCV for Image Processing, Computer Vision, Video Processing and the basics of AI. you will build systems or applications using the techniques learned in the first course as well as some new ones that we cover as we go along. We also cover a substantial amount of Machine Learning and the basics of Deep Learning in this course. We will also build interesting Web Applications as part of the course curriculum. we will start with a theoretical understanding of simple neural nets and gradually move to Deep Neural Nets and Convolutional Neural Networks. Not only will we go over Deep Net architectures used for solving various computer vision problems, we will also go over practical considerations needed to successfully train Deep Neural Networks. These include how to prepare datasets, how to perform sanity checks before embarking on training that can take hours, how to use visualization tools to debug the training process, what workflows to use when the results are not satisfactory, and finally how to deploy your network on the cloud.

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OpenCV University

112K subscribers