Machine Learning

Machine Learning (ML) is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed. It involves algorithms that can identify patterns in data, make predictions, or decisions based on statistical models. Common applications include image recognition, natural language processing, recommendation systems, and predictive analytics.

Also known as: ML, Machine Learning Extraction, ML Extraction, Machine Learning Algorithms, Statistical Learning

Why learn Machine Learning?

Developers should learn machine learning to build intelligent applications that can automate complex tasks, analyze large datasets, and adapt to new information. It is essential for roles in data science, AI development, and any field requiring predictive modeling or pattern recognition, such as finance, healthcare, or e-commerce.

Learning Resources

• course: Machine Learning by Andrew Ng (Coursera)
• docs: Scikit-learn Documentation
• book: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
• tutorial: Machine Learning Tutorial for Beginners (freeCodeCamp)
• course: Introduction to Machine Learning (MIT OpenCourseWare)