Uploaded July 2023 | Updated September 2026, 2 weeks ago
To improve the accuracy of our machine learning classifier, we'll implement another feature where we measure how many visible pixels the drawing has. We do this by first generating a rasterized form of the vectorial drawing. We then count the visible pixels using a simple loop.
The Course: youtube.com/playlist?list=PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4
💻 Code
github.com/gniziemazity/ml-course-phase-2
✔️ Use P5 to follow along
✔️ P6 is the code after this lesson
Recognizing drawings via webcam:
youtu.be/QXB1ytG95gs
⭐️TIMESTAMPS⭐️
00:00 Course Introduction
01:29 Reading the image data
05:00 Getting the pixels
08:29 Debugging
11:49 Complexity feature
16:18 Rescaling the images
To improve the accuracy of our machine learning classifier, we'll implement another feature where we measure how many visible pixels the drawing has. We do this by first generating a rasterized form of the vectorial drawing. We then count the visible pixels using a simple loop.
The Course: youtube.com/playlist?list=PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4
💻 Code
github.com/gniziemazity/ml-course-phase-2
✔️ Use P5 to follow along
✔️ P6 is the code after this lesson
Recognizing drawings via webcam:
youtu.be/QXB1ytG95gs
⭐️TIMESTAMPS⭐️
00:00 Course Introduction
01:29 Reading the image data
05:00 Getting the pixels
08:29 Debugging
11:49 Complexity feature
16:18 Rescaling the images
![A Virtual World - JavaScript Course: Lesson 1 / 11 [Spatial Graphs]](https://i.ytimg.com/vi/V_C7L7zelz8/mqdefault.jpg "A Virtual World - JavaScript Course: Lesson 1 / 11 [Spatial Graphs]
Welcome to Phase 2 of my Self-Driving Car Course!
You dont need to have watched Phase 1 to start this course. A Virtual World is a standalone course where well construct a virtual environment entirely from the ground up. Get ready to use basic HTML, CSS, and JavaScript to craft this world where self-driving cars (or anything you desire, like Pokémon :-D) can roam freely. Our primary focus will be on generating this dynamic world, with the integration of self-driving car code coming at the end.
This course serves as preparation for Phase 3, Understanding AI, where well delve into neural networks and other advanced AI techniques. By the end of Phase 3, youll comprehend the inner workings of neural networks, the importance of hidden layers, and more. But to get there, we need this sophisticated world to create complex scenarios, as our previous one was too simplistic. So, if youre eagerly anticipating neural networks, please be patient and enjoy Phase 2 in the meantime.
In this phase, youll acquire valuable skills, including mathematics, algorithms, programming, and design—skills that greatly benefited me during my PhD and my time at Microsoft. Im confident theyll boost your career as well.
Heres what youll learn:
* Building a spatial graph from scratch and creating an editor with a dynamic viewport.
* Understanding the mathematics and logic behind user-friendly interfaces in modern software.
* Generating road borders, buildings, and trees using geometry and creating a 3D illusion.
* Implementing road markings to prepare for advanced self-driving challenges.
* Enhancing the world editor for user convenience and maximizing auto-generated content.
* Loading real-world data from openstreetmap for city-based simulations.
* Creating a minimap for navigation in expansive worlds.
Have Fun! :-)
⭐PLAYLISTS ⭐
Phase 1: https://www.youtube.com/playlist?list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
Phase 2: https://www.youtube.com/playlist?list=PLB0Tybl0UNfZtY5IQl1aNwcoOPJNtnPEO
💻CODE💻
https://github.com/gniziemazity/virtual-world
⭐FINAL APP⭐
https://radufromfinland.com/projects/virtualworld
⭐ALL PREREQUISITES⭐
https://www.youtube.com/playlist?list=PLB0Tybl0UNfZ3nnHVg8SJ4uK3R4QD6R0H
⭐Pythagorean Theorem Video⭐
https://youtu.be/iqSlzYXdFzw
⭐Euclidean Distance Video⭐
https://youtu.be/3rPwfmrCwVw
⭐App from Phase 1⭐
https://radufromfinland.com/projects/selfdrivingcar
☕Buy me a Coffee?☕
https://www.buymeacoffee.com/radum
⚡️Join this Channel⚡️
https://youtube.com/@radu/join
⭐Timestamps⭐
00:00 Introduction
05:57 HTML Canvas Project Setup
10:52 What are Spatial Graphs?
12:27 Implementing a Spatial Graph in JavaScript
20:41 Implementing the Graph Functionality
48:28 Outro and Special Thanks to prof. Căiniceanu")
