LEARNING PATH: TensorFlow: Computer Vision with TensorFlow
Navigate the LEARNING PATH: TensorFlow for Computer Vision! Unlock the secrets of image analysis and object recognition using the TensorFlow framework. #TensorFlow #ComputerVision #AIEducation ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2018-03-20
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [August 31st, 2023]
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By the end of this Learning Path, learners will acquire the skills and knowledge to create applications and perform image processing using TensorFlow, understand and optimize various features of TensorFlow by building deep learning state-of-the-art models, learn how to create image processing applications using free tools and libraries, perform advanced image processing with TensorFlow APIs, understand graph tensor which is used for image classification, learn to make use of Python API to classify and train models to identify objects in an image, learn about convolutional neural networks (CNNs) and its architecture, learn to construct the neural network feature extractor to embed images into a dense and rich vector space, learn to construct efficient CNN architectures with CNN Squeeze layers and delayed downsampling, learn about residual learning with skip connections and deep residual blocks, learn to implement a deep residual neural network for image recognition, learn about Google's Inception module and depth-wise separable convolutions, understand how to construct an extreme Inception architecture with TF-Keras, and learn to implement an auxiliary conditional generative adversarial networks (GAN).
lHow does this course contribute to professional growth?
This Learning Path provides professionals with the opportunity to gain a comprehensive understanding of image processing and deep learning using TensorFlow. It covers topics such as graph tensor, convolutional neural networks, residual learning, Google's Inception module, and adversarial neural networks. Professionals will learn how to create image processing applications, optimize various features of TensorFlow, construct efficient CNN architectures, and implement auxiliary conditional generative adversarial networks. By the end of this Learning Path, professionals will have the skills and knowledge to create applications and perform image processing efficiently.
Is this course suitable for preparing further education?
Yes, this Learning Path is suitable for preparing further education. It provides a comprehensive overview of image processing and deep learning techniques, as well as an introduction to TensorFlow and its APIs. It also covers advanced topics such as convolutional neural networks, residual learning, and generative adversarial networks. With the help of this Learning Path, learners will be able to create applications and perform image processing efficiently.
Course Syllabus
Learning Computer Vision with TensorFlow
Advanced Computer Vision with TensorFlow
Course Provider
Provider Udemy's Stats at AZClass
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