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AI_Model.py
import tensorflow as tf
from keras.models import Sequential
from keras.layers import Dense, Dropout
# Build Neural Network
model = Sequential([
Dense(128, activation='relu'),
Dropout(0.2),
Dense(64, activation='relu'),
Dense(10, activation='softmax')
])
# Compile & Train
model.compile(
optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy']
)
model.fit(X_train, y_train,
epochs=10,
batch_size=32)
# Predict
predictions = model.predict(X_test)
print("AI Model Ready!")Master AI Technologies: Comprehensive Courses for Future Innovators
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AIOps
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Machine Learning & NLPAn intelligent assessment platform powered by AI that automatically evaluates answers, provides instant feedback, and generates personalized learning insights for students.
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Reinforcement LearningAn interactive gaming experience featuring AI-powered opponents, adaptive difficulty levels, and intelligent game mechanics using deep learning algorithms.
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Large Language Model APIA sophisticated conversational AI system built with LLM APIs that understands context, provides accurate responses, and learns from interactions to improve user experience.
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