Machine Learning Fundamentals

Machine Learning (ML) is a branch of artificial intelligence (AI) focused on building systems that learn from data. This guide provides an overview of the fundamental concepts and techniques in machine learning.

Key Concepts

• Supervised Learning: Learning from labeled data to make predictions.
• Unsupervised Learning: Learning from unlabeled data to find patterns and relationships.
• Reinforcement Learning: Learning by making decisions and receiving feedback in an environment.

Techniques

• Neural Networks: Models inspired by the human brain, capable of learning complex patterns.
• Support Vector Machines (SVMs): Models that find the best hyperplane to separate data.
• Clustering: Grouping data into clusters based on similarity.

Resources

For more in-depth learning, check out our Machine Learning Course.

Neural Network

Conclusion

Machine learning is a rapidly evolving field with endless possibilities. By understanding the fundamentals, you can start exploring and building your own ML models.