Machine learning (ML) is a transformative field of artificial intelligence (AI) that empowers computers to learn and improve from experience without being explicitly programmed. Unlike traditional programming, where specific instructions are given to perform a task, ML algorithms enable systems to automatically learn patterns and make intelligent decisions based on data.
The significance of machine learning spans a multitude of industries, transforming the way we approach problem solving and decision-making. Consider the following real-world examples.
Healthcare
• Medical diagnosis: ML algorithms analyse patient data to assist in diagnosing diseases such as cancer and predicting patient outcomes.
• Drug discovery: ML accelerates the drug discovery process by identifying potential candidates for new medications.
Marketing
Recommendation systems: ML algorithms power recommendation engines on platforms like Netflix and Amazon, providing personalised suggestions based on user preferences.
Customer segmentation: Businesses use ML to segment customers based on behaviour, enabling targeted marketing campaigns.
Technology
• Speech recognition: Virtual assistants like Siri and Google Assistant utilise ML for accurate speech recognition and natural language processing.
This story is from the May 2024 edition of Open Source For You.
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This story is from the May 2024 edition of Open Source For You.
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