Description
TensorFlow: Advanced Techniques Specialization, Library training course TensorFlowis TensorFlow is an open source platform for machine learning that has a complete and flexible ecosystem of tools and libraries. Using TensorFlow, researchers are able to use the latest machine learning achievements and developers can equip their applications with the power of machine learning. The main application of TensorFlow is in applications such as voice recognition, Google Translate, image recognition and natural language processing. This course is recommended for all software and machine learning engineers who have a basic understanding of TensorFlow and are looking to expand their knowledge and skills by learning the advanced features of TensorFlow.
This course is divided into 4 sub-courses, during which you will gain practical knowledge of TensorFlow. In the first part, you will understand the basic principles and basics of Functional API and you will build non-sequential models, customized loss functions and different layers. In the second part, you will learn how optimization works and how to use GradientTape and Autograph and improve the training process in different environments and with multiple chips and processors. The third part is to know and practice advanced scenarios of computer vision such as object recognition, image segmentation and visual interpretation of convolutions, and the fourth part is to explore generative deep learning and how to use artificial hash in new content generation, automatic encoding, VAEs. and GANs are assigned.
What you will learn:
- Understanding the fundamentals of Functional API and building non-sequential strange models, loss functions and layers
- Learning to optimize in different situations and using GradientTape and Autograph
- Practicing object recognition, image segmentation and visual interpretation of twists
- Exploring generative deep learning to create new content, from style transfer to Ventilator-Associated Events algorithms or VAEs and Generative adversarial networks or GANs
What skills do you acquire:
- Interpretation of the model
- Training loops, loss function and custom layers
- Distribution strategies
- Functional API and building personal and strange models with it
- Use GradientTape for optimization
- And …
Specifications of TensorFlow: Advanced Techniques Specialization:
- Publisher: Coursera
- teacher : Laurence Moroney, Eddy Shyu
- English language
- Education level: Intermediate
- Number: 4 courses
- Duration of the course: with a suggested time of 6 hours per week, approximately 5 months
courses
- Custom Models, Layers, and Loss Functions with TensorFlow
- Custom and Distributed Training with TensorFlow
- Advanced Computer Vision with TensorFlow
- Generative Deep Learning with TensorFlow
prerequisites
- Learners should have a working knowledge of AI and deep learning. They should have intermediate Python skills (understanding of decorators and context managers is preferred) as well as some experience with any deep learning framework (TensorFlow, Keras, or PyTorch). Learners should be proficient in basic calculus, linear algebra, and statistics.
- We highly recommend that you complete the Deep Learning Specialization prior to starting this specialization.
Pictures
Sample video
Installation guide
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English subtitle
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download link
Password file(s): www.downloadly.ir
Size
1.35 GB
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