Examples of using A machine learning in English and their translations into Vietnamese
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Scikit-learn is a machine learning library.
It's a Machine Learning class, and it has 400 people enrolled every time it's offered.
Everything begins with the structure, a projection that a machine learning system will apply.
(2010) built a machine learning model that could predict the human classification of a galaxy based on the characteristics of the image.
IBM, for example, provides financial institutions with a machine learning system on IBM z/OS in order to aid financial risk management.
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According to them, the company has developed a machine learning system that detects and disables'inappropriate behavior' accounts.
It is a machine learning system that helps Google understand the meaning behind queries and serve best-matching search results in response to those queries.
Well, one of the reasons is that in order to train a machine learning algorithm you need a lot of labeled and processed data.
For example, a machine learning model will identify an optimization, then generate and send the recommended new settings to the machine, where it is automatically executed.
First, for the people in both data sources, build a machine learning model that uses digital trace data to predict survey answers.
A machine learning algorithm called"DeepHeart" was used to sift through the data for 70 percent of the study participants to diagnose the remaining 30 percent.
Google built its current algorithm around RankBrain, a machine learning(AI) algorithm Google uses to help sort and improve the search results.
If you're a machine learning engineer, it's easy to start experimenting with and fine-tuning these models by using pre-trained models and weights in either Keras/ Tensorflow or PyTorch.
Combining these two sources of data,they used the survey data to train a machine learning model to predict a person's wealth based on their call records.
Google's X Lab develops a machine learning algorithm that is able to autonomously browse YouTube videos to identify the videos that contain cats.
It is used to combine and superimpose existing images and videos onto source images orvideos using a machine learning technique known as generative adversarial network.
DIAmond Award winner BigML has built a machine learning platform that democratises advanced analytics for companies of all sizes.
Unlike traditional programming where the developer needs to anticipate andcode every potential condition, a machine learning solution effectively adapts the output based upon the data.
Deep learning is a machine learning method, loosely based on how the human brain works, that uses neural networks to solve complex problems.
To compare the brain wave patterns of organoids with those of human brains early in development,the team trained a machine learning algorithm with brain waves recorded from 39 premature babies between six and nine-and-a-half months old.
It's a machine learning algorithm that uses a deep neural network to learn the characteristics of sounds, and then create a completely new sound based on these characteristics.
Researchers at the University of Stanford created a machine learning algorithm that is capable of predicting death with a shocking 90 percent accuracy.
Before deploying a Machine Learning model in production, devise the performance evaluation metrics that should be monitored over time as well as determine the frequency of refreshing the machine learning model.
That means that you can build a machine learning model- for example, to correctly identify an object in a photo is a tree, a car or a cat.
Earlier this week, news broke about Google's RankBrain, a machine learning system that, along with other algorithm factors, helps to determine what the best results will be for a specific query set.
Czech researcher Petr Plechác has developed a machine learning system that determined which portions of Henry VIII were likely written by Shakespeare's contemporary(and long-suspected collaborator) John Fletcher.
The same can be achieved with a Machine Learning algorithm, which looks at data previously labeled by a human,learns from the decision making and can then classify incoming requests on its own.
We might think that one of the advantages of a machine learning approach to the selection of job applicants(along with other human related issues) is that, unlike humans, they do not show bias.