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Course Outline
Introduction to Computer Vision for Government
- Overview of computer vision applications in public sector operations
- Understanding image data and formats for government use
- Challenges in implementing computer vision tasks for government
Introduction to Convolutional Neural Networks (CNNs) for Government
- What are CNNs?
- Architecture of CNNs: Convolutional layers, pooling, and fully connected layers
- How CNNs are utilized in computer vision tasks for government agencies
Hands-On with TensorFlow and Google Colab for Government
- Setting up the environment in Google Colab for government use
- Using TensorFlow for model building in government projects
- Building a simple CNN model in TensorFlow for government applications
Advanced CNN Techniques for Government
- Transfer learning for CNNs in government contexts
- Fine-tuning pre-trained models for specific government tasks
- Data augmentation techniques to improve model performance for government datasets
Image Preprocessing and Augmentation for Government
- Image preprocessing techniques (scaling, normalization, etc.) for government data
- Augmenting image data to enhance model training in government applications
- Using TensorFlow’s image data pipeline for government projects
Building and Deploying Computer Vision Models for Government
- Training CNNs for image classification in government settings
- Evaluating and validating model performance for government standards
- Deploying models to production environments in government agencies
Real-World Applications of Computer Vision for Government
- Computer vision in healthcare, retail, and security for government operations
- AI-powered object detection and recognition for government use cases
- Using CNNs for face and gesture recognition in government applications
Summary and Next Steps for Government
Requirements
- Experience with Python programming for government applications
- Understanding of deep learning concepts and their application in public sector projects
- Basic knowledge of convolutional neural networks (CNNs) and their relevance to government workflows
Audience
- Data scientists working in the public sector
- AI practitioners focused on government projects
21 Hours
Testimonials (1)
I genuinely enjoyed the hands-on approach.
