import numpy as np import tensorflow as tf import matplotlib.pyplot as plt x_train = [1, 2, 3, 4] y_train = [0, -1, -2, -3] tf.model = tf.keras.Sequential() tf.model.add(tf.keras.layers.Dense(units=1, input_dim=1)) sgd = tf.keras.optimizers.SGD(lr=0.1) tf.model.compile(loss='mse', optimizer=sgd) tf.model.summary() history = tf.model.fit(x_train, y_train, epochs=100) y_predict = tf.model.predict(..