Convolutional Neural Networks in TensorFlow
Master CNN implementation in TensorFlow for computer vision tasks with advanced techniques and best practices.
Master CNN implementation in TensorFlow for computer vision tasks with advanced techniques and best practices.
This comprehensive course teaches advanced techniques for building and optimizing convolutional neural networks using TensorFlow. Students learn to work with real-world image datasets, implement data augmentation, apply transfer learning, and handle multiclass classification. The curriculum emphasizes practical implementation skills while addressing common challenges like overfitting through hands-on programming assignments.
4.7
(8,124 ratings)
1,51,835 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 4 more
Powered by
What you'll learn
Implement CNNs for large-scale image classification
Apply data augmentation to prevent overfitting
Utilize transfer learning with pre-trained models
Develop multiclass classification systems
Optimize model performance using advanced techniques
Skills you'll gain
This course includes:
0.85 Hours PreRecorded video
8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This course provides in-depth training in implementing convolutional neural networks using TensorFlow. Beginning with large-scale image classification, students progress through advanced topics including data augmentation, transfer learning, and multiclass classification. The curriculum combines theoretical understanding with extensive hands-on practice, featuring real-world datasets and practical implementation challenges.
Exploring a Larger Dataset Module 1
Module 1 · 3 Hours to complete
Augmentation: A technique to avoid overfitting Module 2
Module 2 · 5 Hours to complete
Transfer Learning Module 3
Module 3 · 3 Hours to complete
Multiclass Classifications Module 4
Module 4 · 3 Hours to complete
Fee Structure
Instructor
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.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
4.7 course rating
8,124 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.