Artificial Intelligence

 Artificial Intelligence

Artificial intelligence (AI) involves creating intelligent machines that can perform tasks that typically require human intelligence, such as speech recognition, decision-making, and natural language processing. It typically involves using machine learning frameworks and libraries such as TensorFlow, PyTorch, and Scikit-Learn to train and deploy AI models.

Example of training a machine learning model using TensorFlow in Python:

import tensorflow as tf

# Load the MNIST dataset

mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()

# Preprocess the data

x_train, x_test = x_train / 255.0, x_test / 255.0

# Define the model

model = tf.keras.models.Sequential([

  tf.keras.layers.Flatten(input_shape=(28, 28)),

  tf.keras.layers.Dense(128, activation='relu'),

  tf.keras.layers.Dropout(0.2),

  tf.keras.layers.Dense(10)

])

# Define the loss function and optimizer

loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)

optimizer = tf.keras.optimizers.Adam()

# Compile the model

model.compile(optimizer=optimizer, loss=loss_fn, metrics=['accuracy'])

# Train the model

model.fit(x_train, y_train, epochs=5, validation_data=(x_test, y_test))

# Evaluate the model