Examples of using Machine-learning in English and their translations into Chinese
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Control applications can be either rule-based or machine-learning based.
An on-premises machine-learning solution that extracts hidden value from enterprise data.
We want to remove that manual part for the experts andoffload all feature engineering to a machine-learning model.”.
Next, they trained a machine-learning algorithm to recognize various types of clothing and accessories in images.
Tamr's software takes in huge amounts of“unclean” data anduses machine-learning technology to clean it up and make it more useable.
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The system is a machine-learning system, meaning that it learns to perform tasks by analysing training data.
They gathered their data from 210 healthy adults,and then trained a machine-learning algorithm to detect distinct regional“fingerprints.”.
Js builds a machine-learning model to predict and prefetch JavaScript that will be required in each subsequent page.
In this case, a team of mathematicians designed a machine-learning problem called“estimating the maximum” or“EMX.”.
In London, machine-learning technology has been used to identify signs of eye disease and"recommend how patients should be referred for care.".
They also used the data to start building a machine-learning model to predict the specific foods to which people spike.
Today, he leads a team of digital twin developers andhelps build physics-based models that can be combined with machine-learning algorithms.
The review was updated to July 2016 by using a machine-learning method, and a limited update to October 2016 was done.
The machine-learning program used results from the initial stem cell experiments to infer ways that ROCK1 and CDH1 affect iPS cell organization.
Indeed, more efficient methods for retraining machine-learning code should allow AI to be flexible and useful in different contexts.
Machine-learning tools will underpin automated network management and operational processes: Manual processes will not be able to keep pace with requirements.
It also has anintegrated business rules management system and machine-learning engine that can be extended easily with limited software modifications.
It also said that machine-learning and artificial intelligence roles should be added to the critical skills shortage list that qualifies people for Tier 2 visas.
The simulator produces quakes randomly andgenerates data for an open-source machine-learning algorithm- and the system has achieved some surprising results.
The current stable of machine-learning technologies is not good at looking at the context of a given post or user or community group.
Cambridge-headquartered Darktrace, founded in 2013, uses artificial intelligence(AI) and machine-learning technology to detect and counter cyber threats.
But with the rise of machine-learning techniques that allow computers to parse images, the biggest users of cameras will be machines.
The AI-powered drones not only perform the surveillance more safely andefficiently, but their machine-learning technology can also instantly identify anomalies in the data.
Naive Bayes classification is a machine-learning technique that can be used to predict to which category a particular data case belongs.
Predictive analytics refers to the use of statistical tools and machine-learning algorithms to identify past occurrences, understand present outcomes and predict future consequences.
For example, you can create a machine-learning application that distinguishes between millions of animals, based onimages and written descriptions.
In this article, we focus on AI systems that use machine-learning and deep-learning techniques to enhance or create new applications in the automotive industry.
We can see the influence of machine-learning algorithms in social media, web search engines, mobile device spell checkers and self-driving cars.
Recent reports have shown that machine-learning systems are picking up racist and sexist ideas embedded in the language patterns they are fed by human engineers.
The most relevant types of machine-learning algorithms for cognitive IoT apps are forecasting, including time-series forecasting, anomaly detection, and optimization.