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Machine Learning – Modern Computer Vision & Generative AI
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Machine Learning – Modern Computer Vision & Generative AI
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Overview of this book
This is an innovative course tailored for those who aspire to master the dynamic fields of computer vision and generative artificial intelligence. This course offers a deep dive into the world of image recognition, object detection, and the magic of generative AI using tools like KerasCV, Python, TensorFlow, PyTorch, and JAX.
This course guides you from the fundamentals of image classification to the intricacies of object detection, starting with the KerasCV library for deep learning. You'll learn to effectively use and fine-tune pre-trained models, create custom datasets for object detection, using tools like the LabelImg GUI program, and apply these skills to tackle real-world challenges. A key focus is the generative AI segment, particularly on Stable Diffusion, where you'll learn to generate detailed images from text, unlocking your creative potential in this advanced AI domain.
This course offers a progressive learning path from basic concepts to advanced techniques, catering to both professional development and creative pursuits in AI. By the end, you'll have the confidence and tools needed for a variety of applications in the ever-evolving field of generative artificial intelligence.
Table of Contents (8 chapters)
Image Classification, Fine-Tuning and Transfer Learning
Object Detection
Generative AI with Stable Diffusion
Setting Up Your Environment (Appendix/FAQ by Student Request)
Extra Help With Python Coding for Beginners (Appendix/FAQ by Student Request)
Effective Learning Strategies for Machine Learning (Appendix/FAQ by Student Request)
Appendix / FAQ Finale
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