Machine Learning: Modern Computer Vision & Generative AI | Udemy [Update 10/2023]
English | Size: 1.6 GB
Genre: eLearning[/center]

Use KerasCV, Python, Tensorflow, PyTorch, & JAX for Image Recognition, Object Detection, and Stable Diffusion

What you'll learn
Computer vision with KerasCV
How to do image classification / image recognition with a pretrained model and fine-tuning / transfer learning
How to do object detection with a pretrained model and fine-tuning / transfer learning
How to generate images with Stable Diffusion in KerasCV

Welcome to "Machine Learning: Modern Computer Vision & Generative AI," a cutting-edge course that explores the exciting realms of computer vision and generative artificial intelligence using the KerasCV library in Python. This course is designed for aspiring machine learning practitioners who wish to explore the fusion of image analysis and generative modeling in a streamlined and efficient manner.

Course Highlights:

KerasCV Library: We start by harnessing the power of the KerasCV library, which seamlessly integrates with popular deep learning backends like Tensorflow, PyTorch, and JAX. KerasCV simplifies the process of writing deep learning code, making it accessible and user-friendly.

Image Classification: Gain proficiency in image classification techniques. Learn how to leverage pre-trained models with just one line of code, and discover the art of fine-tuning these models to suit your specific datasets and applications.

Object Detection: Dive into the fascinating world of object detection. Master the art of using pre-trained models for object detection tasks with minimal effort. Moreover, explore the process of fine-tuning these models and learn how to create custom object detection datasets using the LabelImg GUI program.

Generative AI with Stable Diffusion: Unleash the creative potential of generative artificial intelligence with Stable Diffusion, a powerful text-to-image model developed by Stability AI. Explore its capabilities in generating images from textual prompts and understand the advantages of KerasCV's implementation, such as XLA compilation and mixed precision support, which push the boundaries of generation speed and quality.

Course Objectives:

Develop a strong foundation in modern computer vision techniques, including image classification and object detection.

Acquire hands-on experience in using pre-trained models and fine-tuning them for specific tasks.

Learn to create custom object detection datasets to tackle real-world problems effectively.

Unlock the world of generative AI with Stable Diffusion, enabling you to generate images from text with state-of-the-art speed and precision.

Enhance your machine learning skills and add valuable tools to your toolkit for various applications, from computer vision projects to generative art and content generation.

Join us on this captivating journey into the realms of modern computer vision and generative AI. Whether you're a seasoned machine learning practitioner or just starting, this course will equip you with the knowledge and skills to tackle complex image analysis and creative AI projects with confidence. Explore the cutting-edge possibilities that KerasCV and Stable Diffusion offer, and bring your AI aspirations to life.

Prerequisites: Basic knowledge of machine learning and Python programming. Familiarity with deep learning concepts is beneficial but not mandatory.

Who this course is for:
Beginner to advanced students and professionals interested in computer vision with KerasCV

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