Machine Learning (ML) is a branch of Artificial Intelligence that trains computers to learn from data without being explicitly programmed. It focuses on building algorithms that improve their performance over time as they process more data.
How Machine Learning Works
Machine learning models start with training data. The system processes the data, looks for patterns, and builds rules based on what it observes. Once trained, the model can make predictions or decisions on new, unseen data.
There are three main types of ML:
- Supervised learning: trained with labelled input-output pairs
- Unsupervised learning: finds structure in unlabelled data
- Reinforcement learning: learns by trial and error based on feedback
Why ML Is Useful
ML helps automate complex decisions that involve too many variables or too much data for humans to process manually. It can recognise images, recommend products, detect fraud, and even generate content.
What makes ML powerful is that it improves over time. With more data and feedback, the model becomes more accurate and useful.
Machine Learning in the Indian Enterprise
Indian businesses are using ML to solve real problems. Banks use it for credit scoring. Logistics firms use it to optimise routes. Healthcare startups use ML to read medical scans. Telecom companies use it to predict churn.
The ease of cloud-based ML tools has lowered the barrier for adoption. Teams can now use pre-trained models or build their own with minimal infrastructure.
What You Should Know
ML projects can fail if the data is poor, the problem is not well-defined, or the output is not interpretable. A well-designed ML system needs more than just code. It needs the right data pipeline, model selection, validation methods, and monitoring.
