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Details for:
[Udemy] Real World 5+ Deep Learning Projects Complete Course
udemy real world 5 deep learning projects complete course
Type:
Other
Files:
100
Size:
304.0 MB
Uploaded On:
Nov. 25, 2024, 7:17 p.m.
Added By:
Firon5
Seeders:
0
Leechers:
0
Info Hash:
2B38193734A14F1AB3763C7E75B9FF08F7B04B2A
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Official Course URL: https://www.udemy.com/course/real-world-5-deep-learning-projects-complete-course/ Course Overview: Dive into the dynamic world of deep learning with Real World 5+ Deep Learning Projects Complete Course. This course equips you with the necessary skills to implement cutting-edge computer vision applications like facial recognition and emotion detection. Utilizing the powerful YOLOv7 algorithm and tools like Roboflow for dataset management and Google Colab for model training, you'll be prepared to tackle real-world problems with confidence. What You'll Learn: - Introduction to Facial Recognition and Emotion Detection: Grasp the real-world significance of these advanced computer vision techniques. - Setting Up the Project Environment: Master the setup of your deep learning environment, ensuring all necessary tools and libraries are at your disposal. - Data Collection and Preprocessing: Gain insights into the methods for data collection and the techniques for optimizing datasets for training. - Annotation of Facial Images and Emotion Labels: Learn the annotation process essential for training accurate and efficient models. - Integration with Roboflow: Harness the power of Roboflow for efficient dataset management and augmentation. - Training YOLOv7 Models: Engage in a comprehensive training workflow, learning how to adjust parameters and monitor model performance. - Model Evaluation and Fine-Tuning: Discover strategies for model evaluation and fine-tuning to achieve optimal performance. - Deployment of the Models: Understand the steps for deploying your models in real-world applications. - Ethical Considerations in Computer Vision: Discuss the ethical implications of deploying facial recognition and emotion detection technologies. Course Benefits: - Expert Instruction: Receive guidance from Arunnachalam Shanmugaraajan, an experienced educator with a strong background in computer vision and AI. - Hands-On Projects: Tackle practical projects to apply what you learn and solidify your knowledge. - Comprehensive Curriculum: Benefit from a curriculum that covers all necessary aspects of deep learning and computer vision applications. - Flexible Learning: Access the course content at any time, allowing for a learning pace that suits your needs. - Certificate of Completion: Earn a certificate that highlights your expertise upon finishing the course. Total Hours of Course: 2 hours 14 minutes Course Size: 304.0 MB Subtitles: English, Persian Who is this course for? This course is designed for students and professionals interested in computer vision and AI, especially those looking to master YOLOv7 for practical applications in facial recognition and emotion detection
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001-Introduction-To-Brain-Tumor-Detection-Using-YOLOv8-Project-NBDa-english-onehack.us.srt
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