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Generative Adversarial Networks (GAN): The Complete Guide

Master data science & ai from fundamentals to advanced concepts with this comprehensive course.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Master the fundamentals of data science & ai
Apply best practices and industry standards
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry Standards
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of data science & ai
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in data science & ai
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

GANs have been one of the most interesting developments in deep learning and machine learning recently. Yann LeCun, a deep learning pioneer, has said that the most important development in recent years has been adversarial training, referring to GANs. GAN stands for generative adversarial network, where 2 neural networks compete with each other.

What is unsupervised learning. Unsupervised learning means we're not trying to map input data to targets, we're just trying to learn the structure of that input data. This course is a comprehensive guide to Generative Adversarial Networks (GANs).

The theories are explained in-depth and in a friendly manner. After each theoretical lesson, we will dive together into a hands-on session, where we will be learning how to code different types of GANs in PyTorch and Tensorflow, which is a very advanced and powerful deep learning framework. In this first course, You will learnGANDCGANWGAN"If you can't implement it, you don't understand it"Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratchOther courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code. After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times.

Provider
Udemy
Estimated Duration
20-40 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AIUiComplete Course

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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