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import numpy as np

data = np.arange(6 * 6).reshape(6, 6)
print(data)

[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]
 [12 13 14 15 16 17]
 [18 19 20 21 22 23]
 [24 …

import csv

import matplotlib.pyplot as plt
import numpy as np


def load_digits(file):
    x = []
    y = []
    with open(file, "r") as f:
        reader = csv.reader(f)
        for line in reader:
            x.append(np.array(line[0 …

import matplotlib.pyplot as plt
import numpy as np
from mlp import (
    ActivationLayer,
    FullyConnectedLayer,
    InputLayer,
    MeanSquaredError,
    MultiLayerPerceptron,
    Sigmoid,
)

np.set_printoptions(precision=3)

x_train = np.array(
    [
        [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0 …

import matplotlib.pyplot as plt
import numpy as np

# 自作 …

import matplotlib.pyplot as plt
import …

import logging

import numpy as np
from fastprogress.fastprogress import master_bar, progress_bar


class Sigmoid:
    def sigmoid(self, x):
        return 1 / (1 + np.exp(-1 * np.clip(x, -709, 709)))

    def activate(self, z):
        return self.sigmoid(z)

    def deactivate(self, a):
        return a * (1 …

import numpy as np


class SimplePerceptron:

    def __init__(self, epochs=20, learning_rate=0.1, persistence=2):
        self.epochs = epochs
        self.learning_rate = learning_rate
        self.persistence = persistence

    def step(self, z):
        return np.where(z >= 0, 1, 0)

    def activate(self, z):
        return self.step(z)

    def _predict(self …