Machine Learning (ML)
Algorithms that learn patterns from data instead of being explicitly programmed.
What is Machine Learning (ML)?
Machine learning is the most successful approach to building AI systems. Instead of writing rules like "if X then Y", you show the algorithm thousands or millions of examples and let it figure out the rules itself.
There are three broad ML categories. **Supervised learning** uses labelled examples (e.g., "these emails are spam, these are not"). **Unsupervised learning** finds patterns without labels (e.g., clustering customers by behaviour). **Reinforcement learning** learns by trial and error in an environment (e.g., game-playing agents).
Most production ML in Indian companies in 2026 is supervised. Classical algorithms — linear regression, decision trees, XGBoost — still dominate. Deep learning (neural networks) is more common for unstructured data like images, text, and audio.
ML is the engine behind most "AI" in production. If you can build, deploy, and monitor ML models, you have the highest-paying intersection of skills in Indian tech.
A demand forecasting model at a Tier-2 D2C brand predicts how many units of each SKU will sell next week based on past sales, weather, regional festivals, and promotions. The forecast drives inventory + ad-spend allocation.
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