Teaching Neural Networks to Illustrate: A Complete Guide to Training Python-Based AI for Drawing
Created by Team Mammoth
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80 lectures
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Skill level
All levels
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Sections
12
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Lectures
80
04
Instructor
Team Mammoth
What's inside
This course includes.
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12
Sections
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Certificate of completion
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Mobile and desktop access
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AI learning assistance
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Course content
Curriculum & lectures.
+ 00 Course Overview 5 lectures
00 Project Preview
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02 Project 2 Preview
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03 Project 3 Overview
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04 What You'll Need
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+ 01 Code Python on the Web 3 lectures
01.01 What Is Google Colab
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01.02 What If I Get Errors
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01.03 How Do I Terminate A Session
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+ 01a Python Language Fundamentals 21 lectures
00. Intro
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01. Introduction To Python
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02. Variables
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02b. Variables Examples
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03. Type Conversion Examples
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04. Operators
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05. Operators Examples
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06. Collections
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07. Lists
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08. Multidimensional List Examples
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09. Tuples Examples
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10. Dictionaries Examples
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11. Ranges Examples
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12. Conditionals
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13. If Statement Examples
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14. If Statement Variants Examples
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15. Loops
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16. While Loops Examples
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17. For Loops Examples
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18. Functions
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19. Functions Examples
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+ 02 Collect and Process Data 6 lectures
01 Load Drawings Dataset
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02 Label Data
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03 Build A Training Dataset
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04 Visualize Dataset
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05 Batch And Shuffle Data
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+ 03 Build a Generative Neural Network 3 lectures
01 Build A Generator
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02 Generate Noise
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+ 03a Generative Neural Network Fundamentals. 9 lectures
01 What Is A Generative Neural Network
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02 What Is A Convolutional Neural Network
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03 How To Build A Convolutional Neural Network
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04 How To Build A Dense Layer
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05 How To Build A Batch Normalization Layer
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06 Leaky Relu Activation Function
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07 Transposed Convolution Layer
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08 Hyperbolic Tangent (Tanh) Activation Function
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+ 04 Build a Discriminator Neural Network 3 lectures
00 How Do You Build A Discriminator
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01 Build A Discriminator
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+ 05 Evaluate the Model's Performance 5 lectures
00 Performance Of A Machine Learning Algorithm
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01 Calculate Loss
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02 Assign Optimizers
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02A What Is The Adam Optimizer
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+ 06 Train the Model to Draw 4 lectures
01 Build A Training Step
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02 Train The Model
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03 Visualize Training
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+ 07 Test the Model's Drawing Ability 2 lectures
01 Test The Model
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+ 08 Build an Image Style Transfer Project 11 lectures
00 Style Transfer Project Overview
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01 Load The Model
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02 Load Images
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03 Reformat Image For Machine Learning
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04 Load Original And Style Images
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05 Display Processed Images
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06 Extract Image Features
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07 Calculate The Style Representation
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08 Optimize The Model
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09 Use Machine Learning To Transfer Image Style
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+ 09 Build an Image Approximation Project 8 lectures
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01 Load And Process Image
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03 Visualize Training Dataset
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02 Build A Training Dataset
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04 Build A Testing Dataset
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05 Build A Neural Network
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06 Train The Neural Network
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07 Visualize Image Approximation Results
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Instructors
Taught by people who ship.
Team Mammoth
Instructor
Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.
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