maxpagels

import numpy as np
from sklearn import linear_model

n_samples, n_features = 1, 500
y = np.random.randn(n_samples)
X = np.random.randn(n_samples, n_features)
clf = linear_model.SGDRegressor()

import time

endolith

"""
Train a neural network to implement the discrete Fourier transform
"""
import matplotlib.pyplot as plt
import numpy as np
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential

N = 32
batch = 10000