Machine Learning is a subset of Artificial Intelligence (AI) that focuses on building systems that learn from data. This page provides an overview of machine learning tutorials, including the fundamentals and advanced concepts.
Introduction to Machine Learning
Machine learning is the process of teaching computers to learn from data, without being explicitly programmed. It is widely used in various fields such as healthcare, finance, and marketing.
Key Concepts
- Supervised Learning: Learning from labeled data, where the algorithm learns to predict outcomes based on input features.
- Unsupervised Learning: Learning from unlabeled data, where the algorithm tries to find patterns and relationships in the data.
- Reinforcement Learning: Learning by making decisions and receiving rewards or penalties.
Machine Learning Tutorials
1. Basics of Machine Learning
This tutorial covers the fundamental concepts of machine learning, including data preprocessing, model selection, and evaluation.
2. Deep Learning with TensorFlow
TensorFlow is an open-source machine learning framework developed by Google. This tutorial guides you through building deep learning models using TensorFlow.
3. Natural Language Processing with PyTorch
Natural Language Processing (NLP) is a field of AI that focuses on the interaction between computers and human language. This tutorial introduces NLP with PyTorch, a popular deep learning library.
Resources
For further reading, you can explore the following resources: