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.
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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.
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.
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What's inside
Learning objectives
- 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
- 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
Syllabus
Introduction
Introduction & Outline
How to Succeed in This Course
Where to Get the Code
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Syllabus
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Activities
Complete beginner-friendly tutorials on image classification
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Enhance practical skills and apply theoretical knowledge.
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Image Classification
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Find tutorials or online courses that cover image classification with KerasCV.
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Follow the tutorials step-by-step and complete the exercises.
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Experiment with different parameters and datasets to observe their impact.
Practice object detection with pre-trained models
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Reinforce object detection techniques and improve accuracy.
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Object Detection
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-
Set up a development environment with KerasCV and a pre-trained object detection model.
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Collect a dataset of images with various objects.
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Fine-tune the pre-trained model on your dataset to improve its performance.
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Evaluate the fine-tuned model on a validation set to assess its accuracy.
Create a blog post or article summarizing generative AI concepts
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Solidify understanding by explaining concepts to others.
Browse courses on
Generative AI
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Research and gather information about generative AI.
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Organize your thoughts and create an outline for your blog post or article.
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Write the content, ensuring clarity and accuracy.
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Edit and proofread your work.
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Publish your blog post or article on a platform of your choice.
Three other activities
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Build a project using Stable Diffusion to generate images from text prompts
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Apply knowledge to a real-world task and foster creativity.
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Generative AI
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Install Stable Diffusion and familiarize yourself with its interface.
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Experiment with different text prompts and settings to generate images.
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Create a collection of generated images that demonstrate your understanding of Stable Diffusion's capabilities.
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Share your project with others and get feedback.
Attend a workshop on advanced computer vision techniques
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Learn from experts and expand knowledge beyond the course.
Browse courses on
Computer Vision
Show steps
-
Research and identify workshops that align with your interests.
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Register for the workshop and prepare any necessary materials.
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Attend the workshop and actively participate in discussions and activities.
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Follow up with the workshop organizers or speakers to continue learning.
Join a study group or online forum to discuss course topics
Show steps
Enhance understanding through peer-to-peer interactions.
Browse courses on
Computer Vision
Show steps
-
Join a study group or online forum related to computer vision.
-
Actively participate in discussions, ask questions, and share your insights.
-
Collaborate with others on projects or assignments.
Complete beginner-friendly tutorials on image classification
Show steps
Enhance practical skills and apply theoretical knowledge.
Browse courses on
Image Classification
Show steps
- Find tutorials or online courses that cover image classification with KerasCV.
- Follow the tutorials step-by-step and complete the exercises.
- Experiment with different parameters and datasets to observe their impact.
Practice object detection with pre-trained models
Show steps
Reinforce object detection techniques and improve accuracy.
Browse courses on
Object Detection
Show steps
- Set up a development environment with KerasCV and a pre-trained object detection model.
- Collect a dataset of images with various objects.
- Fine-tune the pre-trained model on your dataset to improve its performance.
- Evaluate the fine-tuned model on a validation set to assess its accuracy.
Create a blog post or article summarizing generative AI concepts
Show steps
Solidify understanding by explaining concepts to others.
Browse courses on
Generative AI
Show steps
- Research and gather information about generative AI.
- Organize your thoughts and create an outline for your blog post or article.
- Write the content, ensuring clarity and accuracy.
- Edit and proofread your work.
- Publish your blog post or article on a platform of your choice.
Build a project using Stable Diffusion to generate images from text prompts
Show steps
Apply knowledge to a real-world task and foster creativity.
Browse courses on
Generative AI
Show steps
- Install Stable Diffusion and familiarize yourself with its interface.
- Experiment with different text prompts and settings to generate images.
- Create a collection of generated images that demonstrate your understanding of Stable Diffusion's capabilities.
- Share your project with others and get feedback.
Attend a workshop on advanced computer vision techniques
Show steps
Learn from experts and expand knowledge beyond the course.
Browse courses on
Computer Vision
Show steps
- Research and identify workshops that align with your interests.
- Register for the workshop and prepare any necessary materials.
- Attend the workshop and actively participate in discussions and activities.
- Follow up with the workshop organizers or speakers to continue learning.
Join a study group or online forum to discuss course topics
Show steps
Enhance understanding through peer-to-peer interactions.
Browse courses on
Computer Vision
Show steps
- Join a study group or online forum related to computer vision.
- Actively participate in discussions, ask questions, and share your insights.
- Collaborate with others on projects or assignments.
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