Model.fit(X,y echos=5) error

[Krish9575]

int this below code when i was following your video code its showing error --> its showing error that mx_ndim==2 and found==1 in fit model at step 3 : 3.1--error and 3.2 --> is runs

why???

import numpy as np
import matplotlib.pyplot as plt

create features

X= np.array([-7.0, -4.0, -1.0, 2.0, 5.0, 8.0, 11.0, 14.0,])

Create labels

y= np.array([3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0 ,24.0])

turn our Numpy arrays into tensor

X= tf.cast(tf.constant(X),dtype=tf.float32)

y= tf.cast(tf.constant(y), dtype=tf.float32)

tf.random.set_seed(42)

1. creating a model using sequential API

model =tf.keras.Sequential([
tf.keras.layers.Dense(1)
])

2 . Compile the model

model.compile(loss= tf.keras.losses.mae, # mae i short form of mean absolute error
optimizer= tf.keras.optimizers.SGD(),
# SGD= stochastic gradient descent
metrics=["mae"]

           )

3. Fit the model

3.1 ===> model.fit(X,y,epochs=5);

3.2==> model.fit(tf.reshape(X,shape=(-1,1)),y, epochs=5)

[yadukrishnanp2001]

I also had this error.
very helpfull C:

[yadukrishnanp2001]

Can you please explain how we change (-1,1) to other values according to the model...