Examples of using Machine learning model in English and their translations into Bulgarian
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Computer
Machine Learning Models.
(2010) used the Galaxy Zoo classifications to train a machine learning model to do galaxy classification.
Next, use that machine learning model to impute the survey answers of everyone in the digital trace data.
Then, for a subset of the images, the Galaxy Zoo labels are used to train a machine learning model.
The machine learning models implemented can range from simple linear models to complex artificial neural networks.
(2010) used the Galaxy Zoo classifications to train a machine learning model to do galaxy classification.
Human-in-the-loop(HITL) is a branch of artificial intelligence that leverages both human andmachine intelligence to create machine learning models.
New research has revealed that machine learning models for personalized medicine dosing leak patients' genetic markers.
It combines machine learning, image recognition,and several diverse machine learning models, according to the company.
The new version includes enhanced machine learning models to make Acronis True Image 2020 even more effective at stopping cyberthreats of all kinds.
Then, for a subset of the images,the Galaxy Zoo labels are used to train a machine learning model.
The researchers studied the genetic basis of autism by applying the machine learning model to a treasure trove of genetic data called the Simons Simplex Collection.
The use of machine learning models allows around hundred variables to be analyzed and only the most relevant variables to model GDP growth are kept.
These include workshops,long-term projects with a practical focus on developing Machine Learning models and participating in international conferences.
More specifically, they used their machine learning model, which was trained on their sample of about 1,000 people, to predict the wealth of all 1.5 million people in the call records.
Also, these projects can be done with open calls,whereby researchers compete to create machine learning models with the greatest predictive performance.
The behavior-based and cloud-powered machine learning models included in Windows Defender detected the trojan attack in its early stage, the researchers said.
The study concluded that over 30 percent of surgeries to remove these benign lesions could have been avoided by incorporating this machine learning model into general diagnostic practices.
Then, they used this hand-labeled data to create a machine learning model that could infer the sentiment of a post based on its characteristics.
Also, the machine learning models in these projects can be solicited with open calls,whereby researchers compete to create machine learning models with the greatest predictive performance.
First, for the people in both data sources, build a machine learning model that uses digital trace data to predict survey answers.
Also, the machine learning models in these projects can be solicited with open calls,whereby researchers compete to create machine learning models with the greatest predictive performance.
First, for the people in both data sources, build a machine learning model that uses the big data source to predict survey answers.
Researchers interested in creating what I have calledcomputer-assisted human computation systems(e.g., systems that use human labels to train a machine learning model) might be interested in Shamir et al.
Xnor had developed a way to run large machine learning models without requiring the computing resources and power normally needed for such data-intensive work.
At that point,researchers need to build a computer-assisted human computation system in which human classifications are used to train a machine learning model that can then be applied to virtually unlimited amounts of data.
Building a machine learning model that can correctly reproduce the human classifications is itself a hard problem, but fortunately there are already excellent books dedicated to this topic(Hastie, Tibshirani, and Friedman 2009; Murphy 2012; James et al. 2013).
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.
The features in Banerji and colleagues' machine learning model were more complex than those in my toy example- for example, she used features like“de Vaucouleurs fit axial ratio”- and her model was not logistic regression, it was an artificial neural network.
Researchers interested in creating what I have called computer-assisted human computation systems(e.g.,systems that use human labels to train a machine learning model) might be interested in Shamir et al.