AI Development

import tensorflow as tf
from tensorflow.keras import layers

class NeuralNetwork:
    def __init__(self):
        self.model = tf.keras.Sequential([
            layers.Dense(128, activation='relu', input_shape=(784,)),
            layers.Dropout(0.2),
            layers.Dense(64, activation='relu'),
            layers.Dropout(0.2),
            layers.Dense(10, activation='softmax')
        ])
        
        self.model.compile(
            optimizer='adam',
            loss='sparse_categorical_crossentropy',
            metrics=['accuracy']
        )

    def train(self, x_train, y_train, epochs=10):
        return self.model.fit(
            x_train, y_train,
            epochs=epochs,
            validation_split=0.2
        )

    def predict(self, x):
        return self.model.predict(x)