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ASIN : B0BKQMTXCC
Publication date : October 26, 2022
Language : English
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Print length : 1000 pages
Are you looking to dive into the world of deep learning for computer vision but don’t know where to start? Look no further! In this post, we will explore practical deep learning techniques using Python for computer vision tasks.
Computer vision is a field of artificial intelligence that enables computers to interpret and understand the visual world. Deep learning, a subset of machine learning, has revolutionized the field of computer vision by allowing machines to learn complex patterns and features from large amounts of data.
In this post, we will cover the following topics:
1. Introduction to deep learning for computer vision
2. Setting up your development environment with Python and popular deep learning libraries such as TensorFlow and PyTorch
3. Preprocessing and augmenting image data for deep learning tasks
4. Building and training convolutional neural networks (CNNs) for image classification
5. Fine-tuning pre-trained models for transfer learning
6. Object detection using popular frameworks like YOLO and SSD
7. Image segmentation with semantic and instance segmentation models
By the end of this post, you will have a solid understanding of practical deep learning techniques for computer vision and be able to apply them to your own projects. So, grab your Python notebook and let’s get started on our deep learning journey!
#Practical #Deep #Learning #Computer #Vision #Python
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