👉 Like computing is a type of machine learning that focuses on building models to perform tasks by learning from data, rather than relying solely on handcrafted rules. It involves training algorithms on large datasets to identify patterns and make predictions or decisions without explicit programming. Unlike traditional computing, which follows predefined instructions, like computing leverages statistical methods and neural networks to generalize from examples, enabling it to handle complex tasks like image recognition, natural language processing, and decision-making in dynamic environments. This approach allows systems to improve their performance over time as they are exposed to more data, making them adaptable and efficient in real-world applications.
