That's a very good brief capability of Machine learning that has been outlined.
Machine learning has seen a lot of advancements lately, particularly on the multimodal ML allowing systems to integrate and process data from multiple types, like text, images, voice and video.
Even on Human Computer interaction where gesture recognition and brain interfaces are gaining traction. But the development has always been incremental. I think that's the way to go.
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Ramkumar Yaragarla
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Original Message:
Sent: Fri December 13, 2024 02:09 PM
From: Joe Breath
Subject: AI
Machine learning algorithms are trained to recognize patterns in large datasets by analyzing examples and adjusting their internal rules to make better predictions. First, they are given data that's cleaned, organized, and often split into training and testing sets. During training, the algorithm identifies relationships or trends in the data, like how house size and location affect price. Once trained, the model is tested on new data to see how well it predicts outcomes it hasn't seen before. If it doesn't perform well, it's improved by tweaking its settings, adding more data, or refining features. Over time, the algorithm learns to generalize these patterns, making it useful for tasks like predicting stock prices, recommending products, or detecting spam.
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Joe Breath
Original Message:
Sent: Tue November 28, 2023 10:10 AM
From: Muhammad Adnan
Subject: AI
How can machine learning algorithms be trained to recognize patterns in large datasets and make predictions based on that data?
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Muhammad Adnan
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#AIandDSSkills