AI Capstone Project with Deep Learning
Key Takeaways
Builds and compares deep learning models using Keras and PyTorch for real-world scenarios
Original Description
Ready to apply your AI skills in a real-world scenario you can showcase in your portfolio?
During this project, you’ll work with the deep learning skills you’ve acquired throughout the Professional Certificate, and we recommend that you have completed all the previous courses before starting this one.
For this project, you’ll build and compare deep learning models using Keras and PyTorch, and work through a full development pipeline from data loading and augmentation to model training, evaluation, and deployment.
You’ll apply convolutional neural networks (CNNs) and vision transformers to domain-specific challenges. Then, finally, you’ll assess performance using metrics like accuracy, precision, and inference speed.
By the end of the project, you’ll be able to demonstrate your skills in building and comparing models using Keras and PyTorch. Plus, you’ll be able to showcase that you can implement CNNs and vision transformers and evaluate your model’s performance.
If you’re ready to complete a portfolio-worthy capstone project, enroll today!
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Neural Network Basics
View skill →Related Reads
📰
📰
📰
📰
Help Choosing Neural Network Architecture for Matrix Classification
Reddit r/deeplearning
How to Choose the Best Deep Learning Model for Medical Imaging
Medium · Deep Learning
Another Way to Read Neural Geometry
Medium · Data Science
Another Way to Read Neural Geometry
Medium · Deep Learning
🎓
Tutor Explanation
DeepCamp AI