How Does Machine Learning Work? | 吃瓜猎奇 Global

August 10, 2021

AI is the technology behind Apple鈥檚 Siri, a human-like intelligent assistant capable of listening to your requests and questions, determining what you might be interested in based on the meaning behind what you鈥檝e said, and delivering something that would be useful based on its interpretation of your intended meaning.
Machine learning is the technology behind Amazon鈥檚鈥淵ou might also like鈥� recommendations, which utilizes a complex algorithm to predict what products you may want to buy based on your purchase history and a comparison to other Amazon shoppers who bought similar products.

Predicting House Pricing – The system is given a whole series of input data points, like square footage, the number of bedrooms and bathrooms, features of the house, along with an output data point, the value of the house, and the system learns to predict any new house鈥檚 price based on patterns in the previous data sets (i.e. more bedrooms means a higher price).
Image Recognition – The system is shown pictures of cats and dogs, with labels assigned to each image so that it can learn which types of pictures and patterns in pictures represent a cat, and which represent a dog. The system can then be shown new images of cats or dogs, and use its pattern recognition 鈥渆xperience鈥� whether the new image shows a picture of a cat or a dog.

Customer segmentation – Identifying particular customer groups that should be targeted via different marketing strategies.
Recommendation systems – Netflix鈥檚 suggestions for what to watch next, or Amazon鈥檚 suggestions for what to buy next, based on grouping together users that had similar viewing or purchasing patterns.
Anomaly detection – Banks attempting to detect fraudulent financial transactions or Airlines trying to detect defects in mechanical parts.

Transportation – Google and Tesla are both using machine learning technology to power their self-driving cars, including using deep learning processes to help the cars interpret, predict and respond to data needed to drive autonomously.聽
Manufacturing – to reduce process-driven losses, increase their manufacturing capacity by optimizing the production process, and reduce costs via predictive maintenance.
Finance – Financial institutions are using machine learning technology to detect fraudulent transactions and to identify insights in financial data for purposes like advising investors about what and when to trade.
Retail – Retail uses machine learning to power suggestions and recommendation engines (like the aforementioned Netflix recommendations, and Amazon 鈥淵ou might also like鈥� suggestions), as well as to design聽
Healthcare – Healthcare uses machine learning solutions to help doctors more quickly and more accurately , and to via smartphone data.

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