What Is Machine Learning?

Machine Learning enables computers to learn from data without explicit programming. It powers recommendation systems, image recognition, and language translation.

Essential Libraries

import numpy as np        # Numerical computing
import pandas as pd       # Data manipulation
import matplotlib.pyplot as plt  # Visualization
from sklearn import datasets, model_selection, metrics

First ML Model

from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split

# Load and split data
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# Train model
model = LogisticRegression()
model.fit(X_train, y_train)

# Predict and evaluate
predictions = model.predict(X_test)
accuracy = metrics.accuracy_score(y_test, predictions)

Learning Path

Start with scikit-learn, then TensorFlow or PyTorch for deep learning. Practice with Kaggle competitions.

Conclusion

AI is accessible with Python and the right libraries. Start with simple models and increase complexity gradually.