**Diagram**

AttributeError: ‘Sequential’ Object Has No Attribute ‘predict_classes’ error occurs because **“you are using a version of Keras or TensorFlow where ‘predict_classes’ no longer exists.” **In Keras, the **‘predict_classes’** was deprecated in **Keras 2.3.0** and completely removed in **Keras 2.4.0.**

**Reproducing the error**

```
from keras.models import Sequential
model = Sequential()
y_pred = model.predict_classes(validation_data)
```

**Output**

```
AttributeError: 'Sequential' object has no attribute 'predict_classes'
```

**How to Fix it?**

To fix the AttributeError: ‘Sequential’ Object Has No Attribute ‘predict_classes’, you can use the **“argmax”** function from the numpy library along with the **“predict”** method from your **“Sequential”** object. This combination will provide you with the same output as **‘predict_classes’.**

```
import numpy as np
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
# Define the model
model = Sequential()
model.add(Dense(32, activation='relu', input_dim=100))
model.add(Dense(10, activation='softmax'))
# Compile the model
model.compile(optimizer='adam', loss='categorical_crossentropy',
metrics=['accuracy'])
# Assume 'data' is your input for prediction
data = np.random.random((500, 100))
# Use the 'predict' method to get the class probabilities
probabilities = model.predict(data)
# Use numpy's 'argmax' function to get the class predictions
class_predictions = np.argmax(probabilities, axis=-1)
```

**Output**

`16/16 [==============================] - 0s 279us/step`

After running the above code in my console, you can see that the error is successfully fixed!

Alternatively, you can downgrade your Keras or TensorFlow version.

In Python’s deep learning library, Keras, ‘Sequential’ refers to a linear stack of neural network layers that can be created and manipulated easily.

The best practice for making class predictions in recent versions of Keras and TensorFlow is using the **‘predict’** method and the **‘argmax’** function for the numpy library.

That’s it.

Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.