Demystifying Machine Learning vs. Deep Learning: Understanding Differences and Applications

Machine learning (ML) involves algorithms that enable computers to learn from data and make decisions or predictions without explicit programming. Supervised, unsupervised, and reinforcement learning are primary ML techniques used for tasks such as predictive analytics, pattern recognition, and natural language processing (NLP). Applications span diverse fields, including healthcare diagnostics, financial forecasting, and personalized marketing, where ML models leverage labeled datasets to train and improve accuracy over time.

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