{"id":9751,"date":"2026-08-10T10:10:56","date_gmt":"2026-08-10T10:10:56","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-master-computer-vision-deep-learning-in-opencv-and-keras-2025-3\/"},"modified":"2026-08-10T10:10:56","modified_gmt":"2026-08-10T10:10:56","slug":"udemy-master-computer-vision-deep-learning-in-opencv-and-keras-2025-3","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-master-computer-vision-deep-learning-in-opencv-and-keras-2025-3\/","title":{"rendered":"Udemy \u2013 Master Computer Vision & Deep Learning in OpenCV and Keras 2025-3"},"content":{"rendered":"
\n

Description<\/span><\/h2>\n

Master Computer Vision & Deep Learning in OpenCV and Keras Course. This comprehensive, step-by-step course is designed to provide a complete introduction to computer vision and deep learning. In this course, participants will first learn the basics of the Python programming language and its object-oriented concepts. Then, they will advance their knowledge of the Numpy library from beginner to intermediate levels. This will be followed by a comprehensive training on the OpenCV Python library, and participants will learn how to work with images and videos, perform various manipulations on images, and also object and face recognition techniques. After that, topics related to image kernels, artificial neural networks, the constituent elements of artificial neural networks, and the concept of deep learning will be taught theoretically and practically.<\/span><\/p>\n

\n

After mastering the building of artificial neural network models, the course moves on to more advanced topics such as deep neural networks and convolutional neural networks. In this section, participants will put their skills into practice by developing several practical projects using TensorFlow, Keras, and convolutional neural networks. These projects include binary image classification, multi-class image classification, and real-time object and face recognition and classification. During the course, about 50 practical projects will be developed, of which 17 will be done interactively and with the guidance of the instructor, 13 more projects are already included in the course, and about 4 more projects will be added gradually. The instructor is committed to adding at least 2 projects per week to the course content.<\/span><\/p>\n

What you will learn<\/span><\/strong><\/h3>\n