I want to make simple predictions with Keras and I'm not really sure if I am doing it right. My data looks like this:

col1,col2 1.68,237537 1.69,240104 1.70,244885 1.71,246196 1.72,246527 1.73,254588 1.74,255112 1.75,259035 1.76,267229 1.77,267314 1.78,268931 1.79,273497 1.80,273900 1.81,277132 1.82,278066

Now I want to predict col2 by col1 and this is how I'm doing it:

df = pandas.read_csv('data.csv', usecols=[0, 1], header=None)
X = df.iloc[:, :-1].values.astype(np.float64)
y = df.iloc[:, -1:].values.astype(np.float64)
scalarX, scalarY = MinMaxScaler(), MinMaxScaler()
scalarX.fit(X)
scalarY.fit(y.reshape(len(y),1))
X = scalarX.transform(X)
y = scalarY.transform(y.reshape(len(y),1))

model = Sequential()
model.add(Dense(4, input_dim=1, activation='relu'))
model.add(Dense(4, activation='relu'))
model.add(Dense(1, activation='linear'))
model.compile(loss='mse', optimizer='adam')
model.fit(x=X, y=y, epochs=3, verbose=1)
for num in range(1, 21):
    Xnew = np.array([[float(Decimal('2.{}'.format(num)))]])
    ynew = model.predict(Xnew)
    print("X=%s, Predicted=%s" % (Xnew[0], ynew[0]))

I want to make simple predictions with Keras and I'm not really sure if I am doing it right. My data looks like this:

col1,col2
1.68,237537
1.69,240104
1.70,244885
1.71,246196
1.72,246527
1.73,254588
1.74,255112
1.75,259035
1.76,267229
1.77,267314
1.78,268931
1.79,273497
1.80,273900
1.81,277132
1.82,278066

Now, I want to predict col2 by col1 and this is how I'm doing it:

df = pandas.read_csv('data.csv', usecols=[0, 1], header=None)
X = df.iloc[:, :-1].values.astype(np.float64)
y = df.iloc[:, -1:].values.astype(np.float64)
scalarX, scalarY = MinMaxScaler(), MinMaxScaler()
scalarX.fit(X)
scalarY.fit(y.reshape(len(y),1))
X = scalarX.transform(X)
y = scalarY.transform(y.reshape(len(y),1))

model = Sequential()
model.add(Dense(4, input_dim=1, activation='relu'))
model.add(Dense(4, activation='relu'))
model.add(Dense(1, activation='linear'))
model.compile(loss='mse', optimizer='adam')
model.fit(x=X, y=y, epochs=3, verbose=1)
for num in range(1, 21):
    Xnew = np.array([[float(Decimal('2.{}'.format(num)))]])
    ynew = model.predict(Xnew)
    print("X=%s, Predicted=%s" % (Xnew[0], ynew[0]))