
Complete Computer Vision Bootcamp With PyTorch & Tensorflow
Learn Computer Vision with CNN, TensorFlow, and PyTorch — Master Object Detection from Basics to Advanced
What you'll learn
- Master CNN concepts from basics to advanced with TensorFlow & PyTorch.
- Learn object detection models like YOLO and Faster R-CNN.
- Implement real-world computer vision projects step-by-step.
- Gain hands-on experience with data preprocessing and augmentation.
- Build custom CNN models for various computer vision tasks.
- Master transfer learning with pre-trained models like ResNet and VGG
- Gain practical skills with TensorFlow and PyTorch libraries
Requirements
- Basic understanding of Python programming.
- Familiarity with fundamental machine learning concepts.
- Knowledge of basic linear algebra and calculus.
- Understanding of image data and its structure.
- Enthusiasm to learn computer vision with hands-on projects.
About this course
In this comprehensive Complete Computer Vision Bootcamp With PyTorch & Tensorflow course, you will master the fundamentals and advanced concepts of computer vision, focusing on Convolutional Neural Networks (CNN) and object detection models using TensorFlow and PyTorch. This course is designed to equip you with the skills required to build robust computer vision applications from scratch.
This Complete Computer Vision Bootcamp With PyTorch & Tensorflow course emphasizes practical learning through hands-on projects. Each module includes coding exercises, project implementations, and real-world examples to ensure you gain valuable skills. By the end of this course, you will confidently build, train, and deploy computer vision models using TensorFlow and PyTorch. Whether you are a beginner or an experienced practitioner, this course will empower you with the expertise needed to excel in the field of computer vision.
Enroll now and take your computer vision skills to the next level!
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