Python module tensorflow.keras was not found

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The error message “python module tensorflow.keras was not found” means that the TensorFlow Keras module is not installed in your Python environment.

TensorFlow Keras is a high-level neural networks API that is a part of the TensorFlow library. It provides an easier way to build and train deep learning models.

To resolve this issue, you need to install TensorFlow and its Keras module using the following steps:

  1. Open a command prompt or terminal.
  2. Check if you have pip installed by running the command:

    pip --version

    If it is not installed, you can install pip by following the official documentation for your operating system.

  3. Install TensorFlow by running the command:

    pip install tensorflow

    This will install the latest version of TensorFlow in your Python environment.

  4. After installing TensorFlow, you should have access to the tensorflow.keras module. You can import it in your Python script as follows:

    import tensorflow.keras as keras

    Now you can use the functionalities provided by the TensorFlow Keras module in your code.

Here’s an example of a simple neural network model using TensorFlow Keras: 


import tensorflow.keras as keras
import numpy as np

# Define the model architecture
model = keras.Sequential([
  keras.layers.Dense(64, activation='relu', input_shape=(10,)),
  keras.layers.Dense(64, activation='relu'),
  keras.layers.Dense(1, activation='sigmoid')
])

# Compile the model
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# Generate some random training data
x_train = np.random.random((1000, 10))
y_train = np.random.randint(2, size=(1000, 1))

# Train the model
model.fit(x_train, y_train, epochs=10, batch_size=32)

# Make predictions on new data
x_test = np.random.random((100, 10))
predictions = model.predict(x_test)
print(predictions)

This example demonstrates a simple binary classification model using a neural network with two hidden layers.

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