Examples of using Our algorithms in English and their translations into Chinese
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Political
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Ecclesiastic
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Programming
Some of that can come from rules about how we build our algorithms.
At 8 false positives per slide, our algorithms had a sensitivity of 92%.
We want our algorithms to be as good as the best skilled drivers- and, hopefully, better.
And now we're feeding this data through our algorithms to identify lactic acid threshold.”.
Our algorithms automatically split the problem into smaller parts which fit your hardware the best.
We design- and continually improve- our algorithms to provide the most relevant and useful results.
Our algorithms automatically split the problem into smaller parts which fit your hardware the best.
In the last few weeks we changed our algorithms to make that less likely to happen in the future.
Now, our algorithms typically will just weight those words less and just not give you as much credit.
I am glad to see that the other deep learning labs andcompanies are now also heavily using our algorithms.
We're trying to teach our algorithms to think like a human, so we do a lot of serious gaming.
Just as we concern ourselves with who's teaching our children,we also need to pay attention to who's teaching our algorithms.
The more that our algorithms take on, the better that humans are able to perform,” Cinnamon tells us.
We are using principles like those of the human ear,where vibrations are picked up and our algorithms decipher them to determine your specific movements.
What happens when our algorithms select the news we see and we completely miss what others are seeing?
We are using principles like those of the human ear,where vibrations are picked up and our algorithms decipher them to determine your specific movements.
If our algorithms are to develop equally sophisticated behaviours, they too must have the capability to'imagine' and reason about the future.
Much to our surprise, we only required 50- I repeat, only 50-of these composite images to train our algorithms to high efficiencies.
In reality, as our algorithms and sensors become exponentially more accurate and we gather more data, experts project a 99% reduction or more.
Our algorithms were unfairly filtering 600,000 accounts, including some members of Congress, from our search auto-complete and latest results.
Luckily, over time our algorithms have gotten pretty good at recognizing similar content so as to serve users with a diverse range of information.
We improved our algorithms over time until they were able to consider thousands of different factors and understand geographic location on a very detailed level.
Our algorithm has two phases.
For example, our algorithm could distinguish the retinal images of a smoker from that of a non-smoker 71% of the time.
To locate the exact place, our algorithm must inspect each part of the image to locate the existence of a course.
By improving an existing process using existing data, our algorithm avoids the financial and administrative hurdles that can often impede other policy innovations.".
We're constantly working to improve our algorithm in order to provide users with the best directions on Google Maps.”.
To find the exact location, our algorithm must inspect each component of the picture to find the existence of a course.