Artem Ex Machina™: Become Ai Arts Artisan From The Ground Up

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Effectively apply pre-trained models for generative art!

What you'll learn
Become AI art artisan (generative artist)
Build your own GAN from scratch
Train GAN on a selected set of images
Generate beautiful AI art with pre-trained models
Create pieces of AI art with your own models
Understand how Neural Networks and Generative Adversarial Networks (GAN) work
Work in your AI workshop locally (CPU training) or remotely (GPU training)
Start and manage AI painting project
Requirements
Basic familiarity with python programming
Ability to work in a Docker container will be a bonus
Description
Did you know that computers can generate pictorial art Have you ever wondered how can they do that Did you know that the art generated by Artificial Intelligence (AI) has been sold on auctions for thousands of $$$Welcome to Artem Ex Machina! Here you will learn how to become Artificial Intelligence (AI) Artisan by building, training and applying Generative Artificial Networks (GANs) - deep learning networks behind AI generated art. What makes this course unique is the combination of three elements:Building, training and using GANs from scratchApplying pre-trained GANs for beautiful AI ArtsStarting, maintaining and managing AI Arts projectsBy the end of this course you will, therefore, be able to:Build and train GANs using your own set of training imagesCreate pieces of AI Arts with publicly available, FREE, and amazing quality pre-trained GANs modelsUnderstand how Neural Networks, in general, and GANs, in particular, workEffectively manage AI Arts projects To get a taster on the kind of images you'll be able to generate by completing this course, have a look at the logo of this course, which has 6 examples of images generated with GANs :) The course uses Python as a programming language upon which you'll be able to build, train and use your own GANs. Not only you'll gain practical capabilities when it comes to developing and diagnosing these deep learning models but also you'll gain a proper understanding of theory behind them. Since managing and, potentially, sharing your working environment behind GANs is an important part of the workflow of the generative artist, an integral part of the course is provision of AI-Art-compatible Docker containers and teaching you how to effectively use them. Understanding how GANs work combined with the ability to build them, will give you a strong generative artisanship acumen, and hence strong competitive advantage in the world of Data Science. In addition to that you'll learn how to make an effective use of pre-trained models that were trained for thousands of hours, to create high quality art. Therefore, you'll be able to work on your own local computer as well as remote high performance computing service such as Google Colab using Graphic Processing Units! The course is split into 6 sections culminating with a 3 capstone projects that you can add to your portfolio:Introduction. Here you'll learn how to setup your local working environment PLUS how to train and diagnose a hand-written digits GANWhat is a Generative Adversarial Network Here you'll learn how GANs work and how they are trained PLUS how to train and apply GAN of images of clothing AI Arts projects. Here you'll learn how to work locally vs how to work remotely and principles of AI Arts project management PLUS how to efficiently bulk of images for your GAN trainingGAN architectures. Here you'll learn how to build and train GAN models from scratch to produce complex grayscale and colour images GAN+CLIP. Here you'll learn how to use pre-trained models for beautiful AI Arts generationCapstone projects. Here you'll have the chance to complete three capstone projects to consolidate what you've learnt in the course. Start you Artem Ex Machina journey now!

Overview

Section 1: Introduction

Lecture 1 What will you get from the course

Lecture 2 Intro

Lecture 3 B your first GAN training!

Lecture 4 Load a Docker container

Lecture 5 Compile a Docker container

Lecture 6 Connect to a Docker container

Lecture 7 Run a simple GAN training procedure

Lecture 8 Examine the evolution of GAN

Lecture 9 Switch the container on and off

Lecture 10 Change the memory and CPU of your container

Lecture 11 Train your first GAN challenge

Lecture 12 Train your first GAN solution

Section 2: What is a Generative Adversarial Network

Lecture 13 Intro

Lecture 14 What is Deep Learning

Lecture 15 Artificial Neural Networks and their anatomy

Lecture 16 Training an Artificial Neural Network

Lecture 17 What is a Generative Adversarial Network

Lecture 18 Mnist clothing GAN challenge

Lecture 19 Mnist clothing GAN solution

Lecture 20 Create pieces of AI Arts with your own models

Section 3: AI Arts projects

Lecture 21 Intro

Lecture 22 Local CPU vs remote GPU

Lecture 23 Introduction to Google Colab

Lecture 24 Principles of AI arts project management

Lecture 25 Easily collect your custom training images

Section 4: GAN architectures

Lecture 26 Intro

Lecture 27 Unpacking basic GAN architecture

Lecture 28 From scratch handwritten digit GAN

Lecture 29 From scratch handwritten digit GAN: solution

Lecture 30 CNNs & complex GAN architecture

Lecture 31 Grayscale landscape GAN

Lecture 32 Grayscale landscape GAN: solution

Lecture 33 Colour paintings GAN

Lecture 34 Colour painting GAN: solution

Section 5: GAN+CLIP

Lecture 35 Intro

Lecture 36 Introduction to GAN+CLIP

Section 6: Capstone projects

Lecture 37 Intro

Lecture 38 Capstone 1

Lecture 39 Capstone 2

Lecture 40 Capstone 3

Lecture 41 Course summary

Data scientists and analyst that want to be able to build and apply Generative Adversarial Network models,Data scientists and analyst that want to learn or enhance their Deep Learning skills,STEM professionals wanting to expand into emeg word of AI arts,Anyone who wants to learn how to start AI Arts workshop,Anyone interested in AI arts and that wants to understand it

HomePage:

Https://anonymz.com/https://www.udemy.com/course/artem-ex-machina/

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