AI that learns from data.
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Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn patterns from data and use those patterns to make predictions, identify information, or improve task performance without being explicitly programmed with every rule.
Instead of relying only on fixed instructions, machine-learning systems use data to build models that can make predictions or decisions about new information.
How Does Machine Learning Work?
Collect data: Gather relevant information, such as sales records, customer behavior, images, or text.
Prepare the data: Clean and organize the information so the model can learn from it.
Train the model: Use an algorithm to identify patterns and relationships in the data.
Evaluate performance: Test the model on data it has not seen during training.
Make predictions: Apply the trained model to new data.
Improve the model: Update it when appropriate using additional data, evaluation, and feedback.
Types of Machine Learning
Supervised learning: Learns from labeled examples to predict outcomes, such as whether an email is spam.
Unsupervised learning: Finds patterns or groups in unlabeled data, such as customer segments.
Reinforcement learning: Learns strategies by taking actions and receiving rewards or penalties.
Examples of Machine Learning
Recommendations: Suggests products, movies, or music based on patterns in user activity.
Fraud detection: Identifies transactions that may be suspicious.
Forecasting: Predicts sales, demand, or inventory requirements.
Image recognition: Identifies objects and visual features.
Spam filtering: Classifies unwanted emails.
Personalization: Helps tailor content and offers to customer interests.
Example in Ecommerce
A Shopify jewellery store uses machine learning to analyze past sales and customer interactions. The model identifies products frequently purchased together and helps recommend matching necklaces and earrings to relevant shoppers.
The recommendations depend on the quality of the data and may not always be accurate.
Machine Learning vs. Artificial Intelligence
Artificial intelligence: The broader field of creating systems that perform tasks associated with intelligent behavior.
Machine learning: A subset of AI that learns patterns from data.
Deep learning: A subset of machine learning that uses multilayer neural networks.
In short: Machine learning enables computers to learn from data and make predictions or decisions. It powers many everyday technologies, including recommendations, fraud detection, forecasting, and modern AI tools.