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Build Machine Learning Datasets with Unreal Procedural Generation

00a Course Overview

01 Project Preview (3:05)
01B What You'll Need - Unreal Machine Learning (5:40)
02 What Is Machine Learning (5:26)
03 Types Of Machine Learning Models (12:17)
04 What Are Computer Vision And Image Segmentation (5:40)
Source Files

00b Unreal Introduction

00 What Is Unreal Engine 5 (6:12)
01 How To Install UE5 (4:46)
02 How To Debug Unreal (2:26)
Source Files

01 Build a New Unreal Project

01 Build A New Unreal Project (4:37)
02 Navigate The Unreal Editor (9:43)
03 Navigate The Bottom Half (11:46)
Source Files

02 Build Random Levels Automatically with Procedural Generation

01 Build A Procedural Level Tile (8:26)
02 Build More Tiles (6:11)
03 Build A Blueprint To Randomly Place Tiles (8:01)
04 Build A Grid With The Blueprint (7:59)
04 Source Code
05 Get A Random Tile (7:09)
05 Source Code
06 Set Each Tile Position And Rotation (10:10)
06 Source Code
07 Set Each Instance Name (7:11)
07 Source Code

03 Add Realism to the Procedural Level

01 Add Ground Material To Each Tile (2:58)
01 Source Code
02 Add Environment Models (11:15)
02 Source Code
03 Build Flat Materials For Image Segmentation (11:07)
03 Source Code

04 Build a Blueprint to Enter Segmented View

01 Build Input Action (3:48)
01 Source Code
02 Build Press And Release Conditions (8:31)
02 Source Code
03 Build A Materials Data Table (11:09)
03 Source Code
04 Build A Blueprint To Switch Materials (17:36)
04 Source Code

05 Screenshot the Game via Blueprint

00 WindowsEditor Source Code
01 Screenshot The Game Via Blueprint (7:58)
01 Source Code
02 Make Third Person Character Invisible (5:47)
02 Source Code

06 Deep Learning Introduction

01 What Is Deep Learning (7:42)
Source Files

07 Introduction to Python (Prerequisite)

00. Intro To Course And Python (9:57)
01. Variables (19:19)
02. Type Conversion Examples (10:06)
03. Operators (28:54)
04. Collections (8:24)
05. List Examples (19:41)
06. Tuples Examples (8:36)
07. Dictionaries Examples (14:26)
08. Ranges Examples (8:32)
09. Conditionals (6:43)
10. If Statement Examples (21:32)
11. Loops (29:42)
12. Functions (17:01)
13. Parameters And Return Values Examples (13:54)
14. Classes And Objects (34:11)
15. Inheritance Examples (17:29)
16. Static Members Examples (11:05)
17. Summary And Outro (4:08)
Source Code

07b Neural Networks Introduction

01 What Is A Neural Network (8:47)
02 What Is Supervised Learning (11:03)
03 How Does A Machine Learning Agent Learn (7:38)
04 How To Prepare Data (8:53)
05 Performance Of A Machine Learning Algorithm (4:14)
Source Files

08 Prepare Data For Image Segmentation

01 Load Data For Image Segmentation (6:03)
02 Normalize Images (2:39)
03 Load Training Images (7:12)
04 Load Testing Images (4:39)
05 Prepare Data For Image Segmentation (6:27)
06 Visualize Images And Masks (5:22)
Source Files

09 Build A Neural Network For Image Segmentation

01 How Do You Build A Neural Network For Image Segmentation (10:05)
02 Set Up A Neural Network (6:38)
03 Build Neural Network Layers (6:34)
03B What Is The Adam Optimizer (6:15)
04 Compile Optimizer And Loss (2:09)
Source Files

10 Train And Test Image Segmentation

01 Build A Mask (1:36)
02 Visualize Model Progress (5:15)
03 Visualize Model Results (13:38)
04 Plot Model Accuracy (7:51)
05 Test The Neural Network (3:38)
Source Files

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