Celsius to Fahrenheit conversion simple Neural Network
Hard to say without seeing code, but I can imagine several reasons:


You are using an activation function. You want 'linear' or no activation
Learning rate is much too low
Wrong network (should be one dense layer with one weight)
Poor batch size


This works pretty instantly:

from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Nadam

model = Sequential([Dense(1, activation=None, input_shape=[1])])
model.compile(loss='mean_squared_error', optimizer=Nadam(lr=0.1), metrics=['mean_absolute_error'])

F = list(range(-200,200))
C = [(f - 32) * 5 / 9 for f in F]

model.fit(F, C, batch_size=16, epochs=50)

print(model.predict(np.array([300])))
print(model.layers[0].get_weights())


[[148.88893]]
[array([[0.5555556]], dtype=float32), array([-17.777737], dtype=float32)]


300 F -> 148.8889 C, good, and it has learned the conversion is C = 5/9 * F - 17.7778, or C = 5/9 * (F - 32)