Software Development

Machine Learning & Neural Networks with out Libraries – No Black Box Course

Welcome to this No Black Box Machine Learning Course in JavaScript. It’s a course the place we code with out utilizing libraries as a result of it’s the easiest way to be taught all interior workings of a machine studying system and also you’ll enormously enhance your software program growth expertise as properly.

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The objective on this course is to construct an online app that learns to acknowledge drawings. That is section 2, the place we improve the accuracy of the tactic we developed in Part 1. We do that by implementing extra refined options and utilizing different classification strategies (just like the Neural Community). In Part 2 we additionally study Information Cleansing, Confusion Matrices, Geometry and the distinction between Vector and Raster knowledge (pixels).

🎥 No Black Box Part 1 Course:

✏️ Course created by @Radu (PhD in Laptop Science)

📁 Information:
💻 Code:
💻 Ilya’s code:
💻 Neural Community Code:
Part 3 Ballot:

⭐️ Different Sources ⭐️
Recognizer we construct on this course:
Euclidean Distance Video:
Interpolation Video:
Draw the Portal Recreation Tutorial (Impressed from Dr. Unusual):
Why the Circle has the Largest Space:
Recognizing drawings by way of webcam:
Self-driving Automotive Course:
Discord Server:
Scikit-learn documentation:

⭐️ Contents ⭐️
0:00:00 Introduction
0:04:07 Part 1 Code Evaluate
0:23:11 Information Cleansing
0:41:30 Confusion Matrix
1:16:00 Euclidean Distance Marker
1:16:06 Measuring the Elongation
1:39:23 Measuring the Roundness
1:59:20 Vector vs Raster (Pixels)
2:22:40 Neural Networks
3:04:49 Optimizing Neural Networks
3:25:15 Deep Neural Networks

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👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama

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