Machine Learning (ML)

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→ What is Machine Learning (ML)?

Machine learning is a branch of Artificial Intelligence that focuses on developing models and algorithms that let computers learn from data without being explicitly programmed for every task. In simple words, ML teaches the systems to think and understand like humans by learning from the data.

 

Machine Learning is mainly divided into three core types: Supervised, Unsupervised and Reinforcement Learning along with two additional types, Semi-Supervised and Self-Supervised Learning.

  • Supervised Learning: Trains models on labeled data to predict or classify new, unseen data.
  • Unsupervised Learning: Finds patterns or groups in unlabeled data, like clustering or dimensionality reduction.
  • Reinforcement Learning: Learns through trial and error to maximize rewards, ideal for decision-making tasks.

 

→ The 6 Main Benefits of Machine Learning

  • Automation of Tasks
    ML enables systems to perform repetitive or complex tasks automatically — like scanning resumes, processing loans, or tagging images.
  • Faster and Better Decision-Making
    ML models analyze data in real-time to help make quick, accurate decisions based on patterns — even from massive datasets.
  • Improved Personalization
    ML learns from user behavior to provide personalized experiences.
  • Pattern & trend Recognition
    ML finds patterns in data that humans might miss — useful for predictions, forecasting, or insights.
  • Scalability
    Once trained, ML models can handle large volumes of data or users without a big increase in cost or time.
  • Continuous Improvement
    ML systems get smarter with more data — they improve their performance over time without human reprogramming.