Course Title: Real World 5+ Deep Learning Projects Complete Course Using Roboflow and Google Colab
Course Description:
Welcome to the immersive “Learn Facial Recognition And Emotion Detection Using YOLOv7: Course Using Roboflow and Google Colab.” In this comprehensive course, you will embark on a journey to master two cutting-edge applications of computer vision: facial recognition and emotion detection. Utilizing the powerful YOLOv7 algorithm and leveraging the capabilities of Roboflow for efficient dataset management, along with Google Colab for cloud-based model training, you will gain hands-on experience in implementing these technologies in real-world scenarios.
What You Will Learn:
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Introduction to Facial Recognition and Emotion Detection:
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Setting Up the Project Environment:
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Data Collection and Preprocessing:
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Annotation of Facial Images and Emotion Labels:
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Integration with Roboflow:
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Understand how to integrate Roboflow into the project workflow, leveraging its features for efficient dataset management, augmentation, and optimization for both facial recognition and emotion detection.
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Training YOLOv7 Models:
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Explore the end-to-end training workflow of YOLOv7 using the annotated and preprocessed datasets, adjusting parameters, and monitoring model performance for both applications.
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Model Evaluation and Fine-Tuning:
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Learn techniques for evaluating the trained models, fine-tuning parameters for optimal performance, and ensuring robust facial recognition and emotion detection.
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Deployment of the Models:
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Ethical Considerations in Computer Vision:
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Engage in discussions about ethical considerations in computer vision, focusing on privacy, consent, and responsible use of biometric data in facial recognition and emotion detection.
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