One stop guide to implement cutting-edge CNN architectures and build Neural Network models to solve complex problems!
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Learn how to build and train neural network models to solve complex problems.
Implement supervised and unsupervised machine learning in R for neural networks.
Build an image classifier CNN model to understand how different components interact with each other and then learn how to optimize it.
Understand transfer learning and implement award-winning CNN architectures such as VGG, ResNet, and more.
Understand how generative adversarial networks work and how they can create new, unseen images
This comprehensive R: Neural Nets and CNN Architecture in R - Masterclass! curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
What you need before starting this R: Neural Nets and CNN Architecture in R - Masterclass! course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Packt Publishing
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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