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Build Basic Generative Adversarial Networks (GANs) に戻る

deeplearning.ai による Build Basic Generative Adversarial Networks (GANs) の受講者のレビューおよびフィードバック

4.7
1,388件の評価
336件のレビュー

コースについて

In this course, you will: - Learn about GANs and their applications - Understand the intuition behind the fundamental components of GANs - Explore and implement multiple GAN architectures - Build conditional GANs capable of generating examples from determined categories 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. This Specialization provides an accessible pathway for all levels of learners looking to break into the GANs space or apply GANs to their own projects, even without prior familiarity with advanced math and machine learning research....

人気のレビュー

WM
2020年10月1日

The course provides good insight into the world of GANs. I really enjoyed Sharon's explanations which were deep and easy to understand. I really recommend this course to anyone interested in AI.

MS
2020年10月10日

great course, only teaching what's needed, doesn't push you a lot in the coding assignments, as much as it requires you much more work to understand the codes and the science behind it.

フィルター:

Build Basic Generative Adversarial Networks (GANs): 151 - 175 / 344 レビュー

by FAIRUZ F S 0

2021年4月26日

Its so excited to finish this course and i also learn this for my final project

by Gokulakannan S

2020年12月9日

Nice Course but the interpolation technique didn't work in Week 4 assignment 1.

by W F

2020年11月3日

Good content. Assignments are made to be doable in a reasonable amount of time.

by manohar2000

2020年10月17日

Excellent and disentangled course like the style gan. Really neat explanations.

by Diego M G S

2020年10月7日

una profesora increíble, muy facil de entender la teoria, no tanto las formulas

by Mark T

2021年11月11日

great content. Feel like I learned a lot, and coding labs were useful as well.

by Marcin Z

2020年11月26日

Great course, much better than NLP one. They use PyTorch here which is a plus.

by Vishal K

2020年11月18日

Excellent course to understand the basics of GAN and also do cool assignments!

by Blanca H V G

2020年12月18日

Great course. Sharon is a good teacher. Thank you for all material and codes!

by Sangeeta O

2021年11月8日

​Excellent course with basic of GAN ,loss functions and types of GAN covered

by Adam R R - A

2020年11月16日

This was a pretty simple, understandable introduction to GANs. I enjoyed it.

by brightmart

2020年10月7日

Excellent! Easy to understand, and can get hand-on experience of basic GANs.

by Horváth K

2021年4月9日

I wish I could have the same quality courses at my university as well.

by Oleksandr M

2020年12月21日

Great course! An excellent starting point for exploring GANs. Thanks!

by Tim C

2020年12月8日

An absolutely fantastic course with a lot of details and applications

by Shivender K

2020年11月22日

I had a very good hand on experience on GAN with weekly assignments.

by AKASH C

2020年10月9日

A great introductory lesson on GANs. Coding exercises where amazing.

by MUHAMMEDJASEEM P

2022年1月2日

The Course material is very well presented and super easy to follow

by Злобин Я Н

2021年7月8日

Its greate course to start studying GAN's model and architecture

by Junaid W

2021年5月30日

Well Organized and to the point course. Thank you for making it

by Amr A

2020年10月9日

Well organized and informative course on GANs. Thanks very much

by Sumera R

2021年11月26日

Excellent course for those who want to delve into GAN's world.

by Adarsh W

2021年1月11日

Great introduction to GANS but difficult programming exercise.

by Md. A A M

2021年3月17日

Best course. Best Instructor. Best Labs. Highly recommended.