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u(t) is called 60 times per second. t: Elapsed time in seconds. S: Shorthand for Math.sin. C: Shorthand for Math.cos. T: Shorthand for Math.tan. R: Function that generates rgba-strings, usage ex.: R(255, 255, 255, 0.5) c: A 1920x1080 canvas. x: A 2D context for that canvas.
Theme challenge of the month: #cavern

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  • This #neural network stays ordered but teeters on the edge of chaos -- #dweetdream

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  • Gradient Descent (iterative) algorithm used to calculate sqrt(2). The big dots are the two roots -sqrt(2) and +sqrt(2) of equation Y=X**3-X*2. The Gradient Descent is an optimization algorithm for finding a local minimum of a function near a starting point, taking successive steps in the direction of the negative of the gradient. x[n+1]=x[n]−η(∇f)xn where η is the "Learning Rate". Gradient Descent is widely used for training Machine Learning models. #neural #ai
  • u/rodrigo.siqueira
    Simple version that calculates sqrt(2). If you change initial "x" to -1, it will converge to -sqrt(2), that is the other root of the equation Y=X**3-X*2. Code: x = 1; learning_rate = .1; for(i=0;i<50;i++) { x = x - learning_rate * (x**3 - 2*x) } throw(x);

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  • Pulses of a single neuron in a Spiking Neural Network (SNN) using cosine interpolation with 4 intervals: depolarization (rising curve), repolarization (falling curve), refractory (recovery period) and resting potential (continuous line). #neural #ai

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  • Multi-layer fully connected neural network in 110 characters. #neural

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  • Sigmoid activation function used in Artificial Neural Networks. Animation shows changes of neural weights plus a random bias.

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  • A three-way adversarial deep neural network learning to draw a cat.

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