Introduction to Machine Learning
Machine learning is a branch of artificial intelligence that focuses on the development of algorithms that can learn from and make predictions or decisions based on data.
Learn more about AI on our AI Introduction Guide
Basic Concepts
- Data: The foundation of machine learning models, data comes from various sources and is utilized to train algorithms.
- Algorithms: Step-by-step procedures or formulas used for calculation, data processing, and automated reasoning.
- Models: Representations of real-world processes—a machine learning model uses algorithms to find patterns in data.
Explore more about data science principles in our Data Science Principles Guide
Getting Started with Machine Learning
Embarking on a machine learning journey involves selecting the right tools and methodologies. Here's how:
- Define the research question or problem statement.
- Collect and process the data needed for your machine learning task.
- Choose appropriate algorithms for your model.
- Train the model using data, fine-tuning it to improve accuracy.
- Test the model to evaluate its performance and make necessary adjustments.
Visit our Tools Selection Guide for further insights.