Build Better Generative Adversarial Networks (GANs)

via Coursera

Coursera

1499 Courses


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Overview

Embark on a journey to master Generative Adversarial Networks (GANs) with the DeepLearning.AI Generative Adversarial Networks (GANs) Specialization offered through Coursera. This meticulously designed course is your gateway to understanding the revolutionary world of image generation using GANs, from the ground up to the most sophisticated techniques. Whether you're new to the field or looking to upscale your knowledge, this program caters to all levels of learners.

  • Explore the intricacies of evaluating GANs, diving deep into various generative models and their comparative analysis.
  • Master the evaluation of GANs using the Fréchet Inception Distance (FID) method, focusing on assessing the fidelity and diversity of generated images.
  • Uncover and address sources of bias in GANs, acquiring skills to detect and mitigate bias effectively.
  • Gain hands-on experience with the latest in GAN technology - StyleGANs, learning and implementing cutting-edge techniques.

With a comprehensive curriculum that not only delves into the technical aspects of GANs but also explores the social implications such as bias in machine learning, privacy concerns, and more, this specialization prepares you to tackle current challenges and innovate in the field. You'll have the opportunity to train your own GAN models using PyTorch, create striking images, and evaluate various advanced GANs with confidence.

Offered by Coursera and falling under key categories including Machine Learning Courses, Generative Adversarial Networks (GAN) Courses, and PyTorch Courses, this specialization is an unparalleled resource for anyone looking to dive into GANs or apply these powerful models to real-world projects. Start your GANs adventure today and unlock the potential of AI-generated imagery.

Syllabus


Taught by

Sharon Zhou


Tags

provider Coursera

Coursera

1499 Courses


Coursera

pricing Free Online Course (Audit)
language English
duration 29 hours
sessions On-Demand
level Intermediate