- class Conv2D(Layer): """A 2D Convolution Layer. Parameters: ----------- n_filters: in... class Conv2D(Layer): """A 2D Convolution Layer. Parameters: ----------- n_filters: in...
- from __future__ import division, print_function import numpy as np import math from sklearn import dat... from __future__ import division, print_function import numpy as np import math from sklearn import dat...
- from __future__ import print_function, division import matplotlib.pyplot as plt import numpy as np fro... from __future__ import print_function, division import matplotlib.pyplot as plt import numpy as np fro...
- import numpy as np # Collection of activation functions # Reference: https://en.wikipedia.org/wiki/A... import numpy as np # Collection of activation functions # Reference: https://en.wikipedia.org/wiki/A...
- import numpy as np from mlfromscratch.utils import make_diagonal, normalize # Optimizers for models t... import numpy as np from mlfromscratch.utils import make_diagonal, normalize # Optimizers for models t...
- class Flatten(Layer): """ Turns a multidimensional matrix into two-dimensional """ def __init_... class Flatten(Layer): """ Turns a multidimensional matrix into two-dimensional """ def __init_...
- class UpSampling2D(Layer): """ Nearest neighbor up sampling of the input. Repeats the rows and ... class UpSampling2D(Layer): """ Nearest neighbor up sampling of the input. Repeats the rows and ...
- class ConstantPadding2D(Layer): """Adds rows and columns of constant values to the input. Expe... class ConstantPadding2D(Layer): """Adds rows and columns of constant values to the input. Expe...
- from __future__ import print_function, division import numpy as np import copy class ParticleSwarmOpt... from __future__ import print_function, division import numpy as np import copy class ParticleSwarmOpt...
- from __future__ import division, print_function import numpy as np import math import progressbar # I... from __future__ import division, print_function import numpy as np import math import progressbar # I...
- from __future__ import division, print_function import numpy as np import progressbar from mlfromscra... from __future__ import division, print_function import numpy as np import progressbar from mlfromscra...
- from __future__ import print_function, division import numpy as np import math from mlfromscratch.util... from __future__ import print_function, division import numpy as np import math from mlfromscratch.util...
- class RNN(Layer): """A Vanilla Fully-Connected Recurrent Neural Network layer. Parameters: ... class RNN(Layer): """A Vanilla Fully-Connected Recurrent Neural Network layer. Parameters: ...
- activation_functions = { 'relu': ReLU, 'sigmoid': Sigmoid, 'selu': SELU, 'elu': ELU, ... activation_functions = { 'relu': ReLU, 'sigmoid': Sigmoid, 'selu': SELU, 'elu': ELU, ...
- def accuracy_score(y_true, y_pred): """ Compare y_true to y_pred and return the accuracy """ a... def accuracy_score(y_true, y_pred): """ Compare y_true to y_pred and return the accuracy """ a...
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