Back to Advanced Computer Vision with TensorFlow
Learner Reviews & Feedback for Advanced Computer Vision with TensorFlow by DeepLearning.AI
515 ratings
About the Course
In this course, you will:
a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection.
b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images.
c) Implement image segmentation using variations of the fully convolutional network (FCN) including U-Net and d) Mask-RCNN to identify and detect numbers, pets, zombies, and more.
d) Identify which parts of an image are being used by your model to make its predictions using class activation maps and saliency maps and apply these ML interpretation methods to inspect and improve the design of a famous network, AlexNet.
The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models.
This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models.
Top reviews
EN
Oct 1, 2021
I have learnt many useful computer vision algorithms and more importantly applied them myself. In my mind, practical sessions provided during the course makes it one of the best in Coursera platform
LD
Mar 23, 2023
This course is amazing. It is introduced the most important topics in Computer Vision nowadays: from object detection to generative networks. This is a must-to-do in any capacitation on AI field.
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