What is machine learning in simple terms?

It is a method for estimating patterns from examples so software can predict, rank, classify or detect new cases under a defined task.

What is the difference between supervised and unsupervised learning?

Supervised learning uses labels for a target outcome; unsupervised learning explores structure such as clusters or anomalies without that target.

Why do beginners need a baseline?

A baseline shows whether machine learning and added complexity improve meaningfully over a simple rule or historical method.

Overfitting occurs when a model learns training-sample quirks and performs worse on new representative data.

Why can accuracy be misleading?

A model can achieve high accuracy by predicting a common class while failing to find rare, costly events. Metrics must reflect consequences.

What is data leakage?

Leakage is using information during training or evaluation that would not legitimately be available when the real prediction is made.

Which algorithm should a beginner learn first?

Begin with linear or tree-based models and a reproducible evaluation pipeline. Understanding data and errors matters more than starting with a complex neural network.

Marathi · Rusaka

मशीन लर्निंगच्या मूलभूत गोष्टी समजून घेणे: एक नवशिक्या मार्गदर्शक

मशीन लर्निंग हा आर्टिफिशियल इंटेलिजेंसचा एक उपसंच आहे जो संगणकांना डेटावरून शिकण्यास आणि स्पष्टपणे प्रोग्राम न करता निर्णय घेण्यावर लक्ष केंद्रित करतो. या नवशिक्या मार्गदर्शकाचे उद्दिष्ट मशीन लर्निंगच्या मूलभूत गोष्टींना अस्पष्ट करणे आणि या क्षेत्रात स्वारस्य असलेल्यांसाठी एक भक्कम पाया प्रदान करणे आहे.

मशीन लर्निंग हा आर्टिफिशियल इंटेलिजेंसचा एक उपसंच आहे जो संगणकांना डेटावरून शिकण्यास आणि स्पष्टपणे प्रोग्राम न करता निर्णय घेण्यावर लक्ष केंद्रित करतो. या