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Module 12
Applied Deep Learning
1
Understanding CNN Architecture for Image Recognition
Explain the architecture of Convolutional Neural Networks (CNNs) and their application in image recognition
2
Building and Training a CNN for Image Classification
Build and train a CNN for image classification using a deep learning framework
3
RNN Architecture and Sequential Data
Explain the architecture of Recurrent Neural Networks (RNNs) and their application to sequential data
4
Introduction to Transformer Architecture
Describe the high-level concept of the transformer architecture and its impact
5
Understanding Transfer Learning and Its Benefits
Explain the concept of transfer learning and its benefits
6
Fine-tuning Pre-trained Models
Apply a pre-trained model to a new task (fine-tuning) for faster development
7
Real-World AI Applications
Describe real-world AI applications in various domains (e.g., NLP, computer vision)
8
AI Project Lifecycle: From Idea to Deployment
Outline the key steps for planning and executing a simple AI project from problem definition to deployment
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