Главная
Study mode:
on
1
Introduction
2
The decision boundary
3
Weights
4
Biases
5
Hidden layers
6
Programming the network
7
Activation functions
8
Cost
9
Gradient descent example
10
The cost landscape
11
Programming gradient descent
12
It's learning! slowly
13
Calculus example
14
The chain rule
15
Some partial derivatives
16
Backpropagation
17
Digit recognition
18
Drawing our own digits
19
Fashion
20
Doodles
21
The final challenge
Description:
Dive into the world of neural networks with this comprehensive 55-minute video tutorial. Learn how to program a neural network from scratch in C# and train it to recognize doodles and images. Explore key concepts such as decision boundaries, weights, biases, hidden layers, activation functions, cost calculation, and gradient descent. Follow along as the tutorial progresses from basic principles to advanced topics like backpropagation and practical applications in digit recognition, fashion item classification, and doodle identification. Gain hands-on experience by coding your own neural network and testing it on various datasets, including MNIST digits, fashion items, and Google Quick Draw doodles. Conclude with a final challenge to solidify your understanding of neural network creation and training.

How to Create a Neural Network and Train It to Identify Doodles

Sebastian Lague
Add to list
0:00 / 0:00