{"id":9158,"date":"2026-08-10T10:04:13","date_gmt":"2026-08-10T10:04:13","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-convolutional-neural-networks-with-python-2025-2\/"},"modified":"2026-08-10T10:04:13","modified_gmt":"2026-08-10T10:04:13","slug":"udemy-deep-learning-convolutional-neural-networks-with-python-2025-2","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-convolutional-neural-networks-with-python-2025-2\/","title":{"rendered":"Udemy \u2013 Deep Learning : Convolutional Neural Networks with Python 2025-2"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Deep Learning Course: Convolutional Neural Networks with Python. In this comprehensive course, you will start by building deep convolutional neural network architectures from scratch, augmenting the data with various transformations to increase image diversity, optimizing HyperParameteres before training the model to improve performance, validating the model on test images, calculating performance metrics including Accuracy, Precision, Recall, F1 score, and visualizing the Confusion Matrix to see detailed insights into model performance beyond simple metrics. You will then move on to advanced CNN architectures including RESNT, ALEXNET for image classification, UNET, PSPNET encoder-decoder architectures for semantic segmentation, Region-based CNNs for OD, and YOLO CNNs for real-time object detection, sample segmentation, object tracking, and state estimation. Join us in this course, where you will not only understand the core concepts but also open the door to advanced CNN architectures, equipping yourself with the skills to overcome the most challenging computer vision tasks with confidence and expertise. You will follow a complete pipeline for deep learning CNNs for real-world applications.<\/span><\/p>\n

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