Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

A Generative Adversarial Networks (GANs) Specialization made by deeplearning.ai on Coursera

Course notebooks for GANs specializations

This repository contains my full work and notes on Deeplearning.ai GAN Specialization (Generative Adversarial Networks)

Coursera Generative Adversarial Networks (GANs) Specialization

This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman

This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.

Deeplearning.AI Generative Adversarial Networks (GANs) Specialization Solution

Solutions to DeepLearning.AI Generative Adversarial Networks (GANs) Specialization

Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating realistic image, video, and voice outputs. Rooted in game theory, GANs have wide-spread application: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, turning 2D images to 3D, and more. The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more.

Implementing GANs from scratch

This repo contains my coursework, assignments, Slides and Notes for Generative Adversarial Networks (GANs) Specialization by deeplearning.ai on Coursera

No description available

Generative Adversarial Networks (GANs) Specialization by Sharon Zhou on Coursera - My Completed Coursework Repo - All 3 Courses

Gathering the code submissions from the Generative Adversarial Networks (GANs) Specialization @ Coursera https://www.coursera.org/specializations/generative-adversarial-networks-gans

Tensorflow Developer Specialization from beginner to advance level.it include from ANN , CNN, RNN to GANs. From computer vision to Natural Language processing.

Assignment solution for GANs specialization

Coursera-Generative Adversarial Networks (GANs) Specialization

No description available

Homework from the deeplearning.ai Generative Adversarial Networks GAN Specialization on Coursera (In Progress)

Assignments and Solutions to the course on GANs specialisation from Coursera using PyTorch

No description available

Solutions for the assignments of the GAN Specialization on Coursera by Deeplearning.ai

This repository contains solution to DeepLearning.AI Generative Adversarial Networks (GANs) Specialization.

About GANs Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating realistic image, video, and voice outputs. Rooted in game theory, GANs have wide-spread application: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, turning 2D images to 3D, and more.

Assignments of GAN Specialization from deeplearning.ai

This repository contains coursework and projects from the DeepLearning.AI GANs Specialization, covering topics like building GANs, advanced architectures (DCGANs, WGANs, StyleGANs), and applications in data augmentation and image-to-image translation.

My implementation of Deep Learning.AI Specialization on GAN

All the cool Programming Projects and Assignments I did while pursuing my specialization in GANs

The DeepLearning.AI Generative Adversarial Networks GANs Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs.