Theano NumPy This function defines a simple neural network for classification tasks. It uses the Theano library for symbolic computation and gradient descent optimization. Machine learning 2024-12-16 12:14:25 6 views
Theano NumPy This function defines a simple neural network using Theano library for linear transformations and ReLU activation, then predicts the output. Custom function 2024-12-16 12:11:51 3 views
Theano numpy This code uses the Theano library to optimize the coefficients of a polynomial that fits the given data points. It defines a polynomial function and uses mean squared error as the loss function to evaluate the accuracy of the fit. Then, it uses Theano's gradient computation to optimize the coefficients of the polynomial. The type of code 2024-12-16 12:11:35 3 views
Theano NumPy This function generates a random matrix using Theano and performs a dot product with the input matrix. Function 2024-12-16 12:05:06 4 views
Theano Numpy This function uses Theano to generate a random matrix and stores it as a Theano shared variable. Function 2024-12-16 12:03:18 3 views
numpy theano This function takes two integer arguments, generates a random matrix using numpy, converts it to a shared variable using Theano, computes the sum of all elements in the matrix, and returns it. Mathematical calculation function 2024-12-16 11:59:44 4 views
Theano Numpy This function generates a random matrix using Theano's random functions. The size of the matrix is specified by the parameters rows and cols, and the data type is specified by the dtype parameter. The type of code 2024-12-16 11:54:38 3 views
Theano numpy This function takes two numpy matrices as input, performs matrix addition using the Theano library, and returns the resulting matrix. Math 2024-12-16 11:52:05 3 views
numpy theano This function takes two arguments, arg1 and arg2, generates a random matrix of shape (arg1, arg2), and uses Theano to compute the sum of all elements in the matrix. Function 2024-12-16 11:50:04 3 views
Theano NumPy This function builds and trains a simple neural network using Theano. It initializes weights and biases, defines the architecture of the neural network, and uses the sigmoid activation function and softmax output layer. The function also defines the cost function and the prediction function, and uses Theano to compile the function for training. Machine learning 2024-12-16 11:49:07 3 views
