Uploaded February 2023 | Updated September 2026, 2 weeks ago
The simplest machine learning method I can think of is the nearest neighbor classifier. I’ll show you how to implement it in JavaScript and use it for drawing recognition. We’ll add our sketch-pad component to the data visualizer and extract features from it in real-time. I’ll also teach you how to visualize the classification process on the chart.
The Course: youtube.com/playlist?list=PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4
⭐️HOMEWORK⭐️
Try to account for rotation when computing the width and height. Share screenshots and your code on my Discord server:
discord.com/invite/gJFcF5XVn9
Draw for me :-) I will use your data in the future:
Call for help video: youtu.be/Yw2QZ1vq2ek
Data collection tool: radufromfinland.com/projects/ml
⭐️LINKS⭐️
📁 Data
github.com/gniziemazity/drawing-data
💻 Code
tps://github.com/gniziemazity/ml-course
✔️ Use P3 to follow along
✔️ P4 is the code after this lesson
⭐️TIMESTAMPS⭐️
00:00 Introduction
01:19 Adding the Sketchpad Component
06:10 Extracting Features from Sketchpad
10:44 Showing new Features on the Chart
16:46 Better Features
22:11 Problems with Data
26:22 Nearest Neighbor
37:39 Misleading Chart
The simplest machine learning method I can think of is the nearest neighbor classifier. I’ll show you how to implement it in JavaScript and use it for drawing recognition. We’ll add our sketch-pad component to the data visualizer and extract features from it in real-time. I’ll also teach you how to visualize the classification process on the chart.
The Course: youtube.com/playlist?list=PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4
⭐️HOMEWORK⭐️
Try to account for rotation when computing the width and height. Share screenshots and your code on my Discord server:
discord.com/invite/gJFcF5XVn9
Draw for me :-) I will use your data in the future:
Call for help video: youtu.be/Yw2QZ1vq2ek
Data collection tool: radufromfinland.com/projects/ml
⭐️LINKS⭐️
📁 Data
github.com/gniziemazity/drawing-data
💻 Code
tps://github.com/gniziemazity/ml-course
✔️ Use P3 to follow along
✔️ P4 is the code after this lesson
⭐️TIMESTAMPS⭐️
00:00 Introduction
01:19 Adding the Sketchpad Component
06:10 Extracting Features from Sketchpad
10:44 Showing new Features on the Chart
16:46 Better Features
22:11 Problems with Data
26:22 Nearest Neighbor
37:39 Misleading Chart
![A Virtual World - JavaScript Course: Final Lesson [Coding a MiniMap with JavaScript]](https://i.ytimg.com/vi/ecZRuuLjGQA/mqdefault.jpg "A Virtual World - JavaScript Course: Final Lesson [Coding a MiniMap with JavaScript]
Welcome to the course where we build a self-driving car simulation in a virtual world using HTML, CSS and JavaScript. This is the final video of Phase 2. In it, youll learn to load the large world from the last lesson and implement a mini-map.
The mini-map really helps when the world we create is very big. Lets learn to code one using JavaScript and HTML Canvas. 🗺️
Have Fun! :-)
⭐PLAYLIST⭐
https://www.youtube.com/playlist?list=PLB0Tybl0UNfZtY5IQl1aNwcoOPJNtnPEO
⭐FINAL APP⭐
https://radufromfinland.com/projects/virtualworld
💻CODE💻
https://github.com/gniziemazity/virtual-world
10. OpenStreetMap = follow along
11. MiniMap = code after this lesson
⭐ALL PREREQUISITES⭐
https://www.youtube.com/playlist?list=PLB0Tybl0UNfZ3nnHVg8SJ4uK3R4QD6R0H
☕Buy me a Coffee?☕
https://www.buymeacoffee.com/radum
⚡️Join this Channel⚡️
https://youtube.com/@radu/join
⭐Timestamps⭐
00:00 Introduction
00:42 Including the Large World File
02:49 Preparing for the MiniMap
05:48 MiniMap Implementation
07:58 Scaling the MiniMap
11:00 Marking the MiniMap center
11:49 Outro")
