Getting Started with Machine Learning

Machine Learning has become an integral part of modern technology. In this guide, we'll explore the fundamentals and build your first ML model.

Understanding the Basics

Before diving into implementation, it's crucial to understand key ML concepts. Machine Learning is a subset of artificial intelligence that enables systems to learn and improve from experience.

• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Model Training and Validation

Your First ML Model

import sklearn
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

# Prepare your data
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

# Create and train the model
model = LinearRegression()
model.fit(X_train, y_train)