u/aceofspades914in r/programming • Recommends
On “Deep Neural Network from Scratch in Python | FFNN Architecture”
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DNN in Scratch.
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#scratch#neuralnetworks#backpropagation
Neural Networks in Scratch
DhanOS
348 subscribers • 1 video on Hallway
- Recommended by 1 person: 1 in engineering communities.
- Linked in the descriptiondaniel-kukiela/NNfSiX
- May be out of date. Uploaded 6 years ago, in an area where tools change fast.
Intermediate. Assumes working knowledge.
18K views6 years ago1 recommendation
AI and machine learningComputer scienceNeural networks and deep learningAlgorithmsMath for machine learning
An implementation of a deep neural network with backpropagation, SGD, and activation functions built entirely within the Scratch programming language.
Implementation of Neural Network in Scratch programming language. Model includes 2 hidden (Dense) layers, 8 neurons each, ReLU activation functions, 10 neurons in output (Dense) layer with Softmax activation function, Cross-entropy loss, calculating of an accuracy, and full backward pass including derivatives, and loss minimization using backpropagation and simple SGD optimizer. ------ Scratch project files and more: github.com/daniel-kukiela/NNfSiX Full training process at x1 speed: youtu.be/oWhorAstLps Twitter: twitter.com/daniel_kukiela Neural Networks from Scratch in Python book: nnfs.ioWhy it's here
1 person recommends thisWhat people say. Recommended as an impressive demonstration of building a fully functional neural network from scratch in a block-based language.