Mastering Neural Style Transfer: Tensorflow, Keras & Python
Mastering Neural Style Transfer: Tensorflow, Keras & Python, available at $19.99, has an average rating of 4.42, with 33 lectures, based on 6 reviews, and has 119 subscribers.
You will learn about Understand Neural Style Transfer and its application in combining content and style in images. Learn to implement Neural Style Transfer algorithms using Python and Keras. Gain proficiency in image preprocessing techniques and using pre-trained models like VGG19. Understand the concept of loss functions and their role in style transfer optimization. Acquire skills in optimizing style transfer using an optimizer with learning rate decay. Learn to save and display generated images during the optimization process. Gain practical experience in implementing Neural Style Transfer algorithms. This course is ideal for individuals who are Beginners interested in deep learning and computer vision or Students studying computer science, artificial intelligence, or related fields or Professionals looking to enhance their skills in neural style transfer and generative adversarial networks or Developers interested in learning how to implement image processing techniques using Python and Keras or Individuals with a curiosity for creative applications of artificial intelligence in the field of image generation and style transfer It is particularly useful for Beginners interested in deep learning and computer vision or Students studying computer science, artificial intelligence, or related fields or Professionals looking to enhance their skills in neural style transfer and generative adversarial networks or Developers interested in learning how to implement image processing techniques using Python and Keras or Individuals with a curiosity for creative applications of artificial intelligence in the field of image generation and style transfer.
Enroll now: Mastering Neural Style Transfer: Tensorflow, Keras & Python
Summary
Title: Mastering Neural Style Transfer: Tensorflow, Keras & Python
Price: $19.99
Average Rating: 4.42
Number of Lectures: 33
Number of Published Lectures: 33
Number of Curriculum Items: 33
Number of Published Curriculum Objects: 33
Original Price: ₹799
Quality Status: approved
Status: Live
What You Will Learn
- Understand Neural Style Transfer and its application in combining content and style in images.
- Learn to implement Neural Style Transfer algorithms using Python and Keras.
- Gain proficiency in image preprocessing techniques and using pre-trained models like VGG19.
- Understand the concept of loss functions and their role in style transfer optimization.
- Acquire skills in optimizing style transfer using an optimizer with learning rate decay.
- Learn to save and display generated images during the optimization process.
- Gain practical experience in implementing Neural Style Transfer algorithms.
Who Should Attend
- Beginners interested in deep learning and computer vision
- Students studying computer science, artificial intelligence, or related fields
- Professionals looking to enhance their skills in neural style transfer and generative adversarial networks
- Developers interested in learning how to implement image processing techniques using Python and Keras
- Individuals with a curiosity for creative applications of artificial intelligence in the field of image generation and style transfer
Target Audiences
- Beginners interested in deep learning and computer vision
- Students studying computer science, artificial intelligence, or related fields
- Professionals looking to enhance their skills in neural style transfer and generative adversarial networks
- Developers interested in learning how to implement image processing techniques using Python and Keras
- Individuals with a curiosity for creative applications of artificial intelligence in the field of image generation and style transfer
Step into the captivating world of Neural Style Transfer, where ordinary images are transformed into mesmerizing works of art using cutting-edge techniques. Get ready for an immersive journey that will empower you to unleash your creativity and unlock the full potential of this revolutionary technology, guided by experts in the field.
Throughout this comprehensive course, you will explore the fascinating realm of artistic image generation, starting with the fundamentals of Neural Style Transfer and advancing to delve into the realm of advanced generative adversarial networks. Armed with the powerful trio of Google Colab, TensorFlow, and Keras, you’ll have all the tools you need to bring your artistic visions to life.
Unleash your imagination without the constraints of hardware limitations, as you harness the unparalleled computing capabilities of Google Colab’s cloud platform. This means you can focus wholeheartedly on refining your artistry and honing your skills, leaving the technical worries behind.
By the course’s conclusion, you will not only possess a profound understanding of Neural Style Transfer and its practical implementation, but you’ll also have a captivating portfolio of awe-inspiring images that showcase your newfound talent. As the demand for AI-driven image manipulation skyrockets, this course will provide you with the expertise that employers across various industries actively seek.
Embrace a world of boundless creative possibilities and set forth on a rewarding career journey. Enroll now to unlock the gateway to thrilling job opportunities in graphic design, advertising, entertainment, and beyond. Allow your artistic vision to soar as you master the art of Neural Style Transfer, creating captivating visuals that will leave a lasting impression on the world!
Course Curriculum
Chapter 1: Fundamentals
Lecture 1: Introduction
Lecture 2: What is Neural Style Transfer?
Lecture 3: About this Project
Lecture 4: Why Should we Learn?
Lecture 5: Applications
Lecture 6: Why Keras and Python?
Lecture 7: Why Google Colab?
Chapter 2: Model Building and Prediction
Lecture 1: Setup the Working Directory
Lecture 2: Contents in Directory
Lecture 3: Activate GPU
Lecture 4: Checking the availability and usage of GPUs
Lecture 5: Mount Google Drive to Google Colab
Lecture 6: Necessary library imports
Lecture 7: Setting the directory path
Lecture 8: Displaying the base image and the style reference
Lecture 9: Defining the desired dimensions
Lecture 10: Preprocesses an image
Lecture 11: Convert the generated image back to its original format
Lecture 12: Calculate the Gram matrix
Lecture 13: Calculates the style loss
Lecture 14: Calculates the content loss
Lecture 15: Calculates the total variation loss
Lecture 16: Loading the VGG19
Lecture 17: Creating a dictionary
Lecture 18: Building a feature extraction model
Lecture 19: Define the names of the style layers and the content layer
Lecture 20: Set the weights
Lecture 21: Calculates the total loss
Lecture 22: Computes the loss and gradients
Lecture 23: Set up the optimizer
Lecture 24: Preprocess the base image, style reference image, and combination image
Lecture 25: Perform the style transfer optimization loop
Lecture 26: Save and display the final generated image
Instructors
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Karthik Karunakaran, Ph.D.
Transforming Real-World Problems with the Power of AI-ML
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- 2 stars: 1 votes
- 3 stars: 0 votes
- 4 stars: 2 votes
- 5 stars: 3 votes
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