Artificial Intelligence 101
Learn the Future with DARCHUMSTECH 🚀
🧠 What is Artificial Intelligence?
Artificial Intelligence (AI) enables machines to perform tasks requiring human-like intelligence—like problem solving, language understanding, and decision-making.
📚 Types of AI
- Narrow AI: Performs specific tasks (e.g., Siri, Google Maps).
- General AI: Can perform any intellectual task like a human (theoretical).
- Super AI: Surpasses human intelligence (conceptual).
🎯 Applications of AI
- Self-driving cars
- Virtual assistants
- Recommendation systems
- Fraud detection
- Medical diagnostics
📌 Note: AI is designed to enhance human abilities, not replace them.
🔬 Core Concepts in AI
- Machine Learning: Algorithms that learn from data.
- Deep Learning: Brain-like neural networks with many layers.
- NLP: Teaching computers to understand human language.
- Computer Vision: Interpreting visual data like images and videos.
🐍 Python Example: Flower Prediction
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
X, y = load_iris(return_X_y=True)
model = DecisionTreeClassifier()
model.fit(X, y)
sample = [[5.1, 3.5, 1.4, 0.2]]
prediction = model.predict(sample)
print("Predicted Flower:", load_iris().target_names[prediction[0]])
🎯 Challenge:
Swap out DecisionTreeClassifier with RandomForestClassifier and observe the results!
🛠️ Key Libraries for AI in Python
- scikit-learn: Traditional ML
- TensorFlow & PyTorch: Deep Learning
- spaCy / NLTK: NLP tasks
- OpenCV: Computer vision
💡 Conclusion
AI is rapidly changing the world. Begin with basics, practice projects, and you'll be building smart applications in no time.
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