Custom Models, Layers, and Loss Functions with TensorFlow
This course is part of TensorFlow: Advanced Techniques Specialization.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full TensorFlow: Advanced Techniques Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Design and implement custom loss functions for specialized tasks
Create custom layers by extending TensorFlow's base layer class
Build complex model architectures using the Functional API
Implement Siamese networks and residual networks (ResNet)
Develop custom model classes extending TensorFlow's base model
Create custom callbacks for training monitoring and control
Skills you'll gain
This course includes:
2.5 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course focuses on advanced TensorFlow techniques for building custom neural network components. Students learn to create custom models using the Functional API, implement specialized loss functions, design custom layers, and extend the TensorFlow Model class. The curriculum covers advanced topics including Siamese networks, ResNet architecture, and custom callbacks, providing hands-on experience through programming assignments and practical implementations.
Functional APIs Module 1
Module 1 · 7 Hours to complete
Custom Loss Functions Module 2
Module 2 · 7 Hours to complete
Custom Layers Module 3
Module 3 · 7 Hours to complete
Custom Models Module 4
Module 4 · 6 Hours to complete
Bonus Content - Callbacks Module 5
Module 5 · 2 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: TensorFlow: Advanced Techniques Specialization
Instructors
Pioneering AI Educator and Best-Selling Author
Laurence Moroney is an award-winning artificial intelligence researcher and best-selling author dedicated to making AI and machine learning accessible to everyone. As an instructor at DeepLearning.AI, he has taught millions through MOOCs and YouTube, while also serving as a keynote speaker at various events. Moroney is a fellow of the AI Fund and advises several AI startups, leveraging his expertise to foster innovation in the field. Based in Seattle, Washington, he is also an active member of the Science Fiction Writers of America, having authored multiple sci-fi novels and comic books. When not immersed in technology, he enjoys indulging in coffee and exploring creative writing.
Pioneering AI Education and Product Management
Eddy Shyu is a prominent AI Product Manager at Cisco, with a notable background in curriculum development as the former Curriculum Product Manager at DeepLearning.AI. He has played a crucial role in creating approximately 40 online courses focused on artificial intelligence, which have reached over 2 million learners across platforms such as Coursera, DeepLearning.AI, Udacity, and Cisco Networking Academy. Eddy's expertise extends to designing educational content that simplifies complex AI concepts for diverse audiences, ensuring accessibility and engagement in learning. His work includes leading the creation of Andrew Ng’s Machine Learning Specialization, which has become a foundational resource for aspiring AI professionals. With a passion for education and innovation, Eddy continues to shape the future of AI learning and product management, empowering individuals to leverage artificial intelligence effectively in their careers.
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