Concept

• Artificial Intelligence (AI): AI is the broad field of creating systems. These systems carry out tasks that typically required human intelligence. These tasks include reasoning, problem-solving, or decision-making. Example: A chatbot answering questions.
• Machine Learning (ML): A subset of AI. In this field, systems learn patterns from data to make predictions or decisions. This process occurs without explicit programming. Example: Predicting house prices based on historical data.
• Neural Network (NN/ANN): A type of ML model inspired by the human brain. It uses inter connected nodes (Neurons) to process data. Used for task like image recognition.
• Deep Learning (DL): It is a subset of ML. It uses deep neural networks with many layers. These networks handle complex tasks like speech recognition or self-driving car vision.

Key Analogy

AI is the universe. ML is a galaxy. NN is a star system. DL is a specific bright star with many layers.

Python Library Installation

Installed these libraries and verified they work.

import numpy as np
import pandas as pd
import sklearn
import tensorflow as tf

# Verify installations
print("NumPy version:", np.__version__)
print("Pandas version:", pd.__version__)
print("Scikit-learn version:", sklearn.__version__)
print("TensorFlow version:", tf.__version__)

# Simple NumPy array operation to confirm setup
data = np.array([1, 2, 3, 4, 5])
print("Mean of array:", np.mean(data))