Profitech AI

Home
Projects
Clientele
Process
Support
Consultation

import tensorflow as tf
from sklearn.model_selection import train_test_split
import numpy as np

# AI Model Development
def create_neural_network():
    model = tf.keras.Sequential([
        tf.keras.layers.Dense(128, activation='relu'),
        tf.keras.layers.Dropout(0.2),
        tf.keras.layers.Dense(64, activation='relu'),
        tf.keras.layers.Dense(10, activation='softmax')
    ])
    
    model.compile(
        optimizer='adam',
        loss='sparse_categorical_crossentropy',
        metrics=['accuracy']
    )
    
    return model

# Train AI Model
def train_ai_model(X, y):
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
    model = create_neural_network()
    model.fit(X_train, y_train, epochs=100, validation_split=0.2)
    return model

P

Profitech

Subscribe for AI insights

P

Profitech

Stay updated with AI trends