Kursusindhold
Introduction to Neural Networks
Introduction to Neural Networks
2. Neural Network from Scratch
Single Neuron ImplementationChallenge: Creating a NeuronPerceptron LayersChallenge: Creating a PerceptronForward PropagationLoss FunctionBackward PropagationBackpropagation ImplementationModel TrainingChallenge: Training the PerceptronModel EvaluationChallenge: Evaluating the PerceptronNeural Network with scikit-learn
Challenge: Creating a Neuron
Opgave
Swipe to start coding
Your task is to implement the basic structure of a neuron by completing the missing parts.
- Initialize the weights (an array) and bias (a single number) with random values from a uniform distribution in range
[-1, 1)using NumPy. - Compute the weighted sum of the inputs using the dot product, add the bias, and store the result in
input_sum_with_bias. - Apply the sigmoid activation function to
input_sum_with_biasto obtain the neuron's output.
Løsning
Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående mulighederVar alt klart?
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Sektion 2. Kapitel 2
Challenge: Creating a Neuron
Opgave
Swipe to start coding
Your task is to implement the basic structure of a neuron by completing the missing parts.
- Initialize the weights (an array) and bias (a single number) with random values from a uniform distribution in range
[-1, 1)using NumPy. - Compute the weighted sum of the inputs using the dot product, add the bias, and store the result in
input_sum_with_bias. - Apply the sigmoid activation function to
input_sum_with_biasto obtain the neuron's output.
Løsning
Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående mulighederVar alt klart?
Tak for dine kommentarer!
Sektion 2. Kapitel 2
Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder