Udemy

Machine Learning: Modern Computer Vision & Generative AI

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  • 7,146 Students
  • Updated 11/2025
  • Certificate Available
4.7
(949 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
6 Hour(s) 31 Minute(s)
Language
English
Taught by
Lazy Programmer Inc., Lazy Programmer Team
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.7
(949 Ratings)
2 views

Course Overview

Machine Learning: Modern Computer Vision & Generative AI

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

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.

Course Content

  • 9 section(s)
  • 41 lecture(s)
  • Section 1 Introduction
  • Section 2 Image Classification, Fine-Tuning and Transfer Learning
  • Section 3 Object Detection
  • Section 4 Generative AI with Stable Diffusion
  • Section 5 Appendix / FAQ Intro
  • Section 6 Setting Up Your Environment (Appendix/FAQ by Student Request)
  • Section 7 Extra Help With Python Coding for Beginners (Appendix/FAQ by Student Request)
  • Section 8 Effective Learning Strategies for Machine Learning (Appendix/FAQ)
  • Section 9 Appendix / FAQ Finale

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


Reviews

  • S
    Shane Giles
    5.0

    Good explanations and applicable exercises. It was great to be able to follow along and challenge myself along the way. The repetition of following along helped me reinforce the lessons. I can't wait to apply it to some projects I have at work.

  • R
    Romerojnr@Gmail.Com
    1.0

    I've been watching courses here in my free time for a while, and boy, this is bad. It feels like 99% of this material was AI generated, you can see how they try (poorly) to cover it up by using human voice to walk through the examples, with little to no real knowledge of what's happening in the code. Sadly this wave of AI generated scams can only be stopped by *YOU* (reader), do *NOT* purchase this course.

  • R
    Rahul Mane
    5.0

    The course was very useful to upgrade my skills, the content was fabulous and easy to learn. I really liked this course and would definitely recommend it to my friends and colleagues!

  • S
    Shital Ingole
    3.5

    good

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