Examples of using Machine learning can in English and their translations into Chinese
{-}
-
Political
-
Ecclesiastic
-
Programming
Machine learning can be considered a booster to the said technology since their convergence can ensure an incredibly fast analysis of enormous volumes of data.
Machine learning can be employed for predictive analysis and pattern recognition in Big Data.
Machine learning can recognize specific patterns and is able to improve with every task it undertakes.
More to the point, the researchers said, they have now demonstrated that machine learning can dramatically speed the process of discovering new materials.
Through repetition and adjustment, machine learning can exploit large amounts of data and identify complex patterns that may not be evident to humans.
It may be that while machine learning can benefit drug discovery, it will have greater impacts in other areas of chemistry.
Businesses, governments and scientific labs are clamoring to see how machine learning can tackle their problems.
Thinking more systematically, Peter Norvig has argued that machine learning can be used to generate short programs(but not long ones) from training data;
Machine learning can be used across industries, including but not limited to healthcare, automotive, financial services, cloud service providers, and more.
Machine learning can be applied in various functional domains, including image recognition, speech/voice recognition, natural language processing, and autonomous systems.
Machine learning can train a system to detect potential threats while retaining the flexibility that it needs to provide computing power and storage on demand.
If machine learning can improve vessel scoring, then it would enhance the contribution of non-invasive imaging to cardiovascular risk assessment.
Machine learning can enhance relationship intelligence in CRM systems to help sales teams better understand their customers and make a connection with them.
It requires focusing the organization, analyzing business cases to determine where machine learning can add value, and managing the risks of a new methodology.
The organization needs to analyze business cases to determine where machine learning can add the most value while managing the risks of a new methodology.
Apart from disease prediction, there are the few more potential areas like drug discovery or electronic health records where machine learning can improve healthcare industry.
The findings, published May 15 in Nature Communications, suggest that machine learning can add to the expertise and analysis of a neuropathologist.
Last year, the story about the Amazon AI recruiting tool being biased against women was proof that machine learning can mimic human attitudes.
The findings, published May 15 in Nature Communications, suggest that machine learning can augment the expertise and analysis of an expert neuropathologist.
Delivering personalized experiences: Machine learning can automatically tailor messaging based on a user's historical and predicted behavior.