Examples of using Learning algorithm in English and their translations into Hebrew
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Colloquial
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Ecclesiastic
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Computer
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Programming
Learning algorithms should also be as general purpose as possible.
Here is some text that I generated using a deep learning algorithm yesterday.
Deep learning algorithms are the technological foundation of IMedis.
That's something like to the task performed by deep learning algorithms.
Automatic learning algorithms have become a key element in today's world.
Understanding the building blocks in project management based on learning algorithms.
With our deep learning algorithm, it can automatically identify areas of structure in these images.
Artificial intelligence researchers havelong used games to train their machine learning algorithms.
Each of these sentences was generated by a deep learning algorithm to describe each of those pictures.
Thus the learning algorithm defined by the ERM principle consists in solving the above optimization problem.
The software analyzes the information mastering of a user and determines the most favorable learning algorithm.
We have created a machine learning algorithm, which is capable of predicting the chance of a student course dropout with 92% accuracy.
So to teach a computer to see a picture and generate sentences,the marriage between big data and machine learning algorithm has to take another step.
The company has developed a unique platform,based on deep learning algorithms, for processing CT scans and medical text from radiological reports.
The machine learning algorithms use archival EM footage to learn what each fish species looks like from a variety of angles and under a wide range of lighting conditions.
The companies that run campaigns on socialnetworks are at the intersection where machine learning algorithms and advertising technologies meet.
NSA's Skynet machine learning algorithm has possibly aided in the deaths of thousands of civilians in Pakistan from misreading cellular device metadata.
A team of researchers affiliated with several institutions in Germany andthe U.S. has developed a deep learning algorithm that can be used for motion capture of animals of any kind.
Consequently, practical decision-tree learning algorithms are based on heuristics such as the greedyalgorithm where locally-optimal decisions are made at each node.
For example, if the task were determining whether an image contained a certain object,the training data for a supervised learning algorithm would include images with and without that object, each image would have a label designating whether it contained the object.
Machine learning algorithms allow computers to learn and detect patterns in huge amounts of data, establishes the relation between inputs and outputs, between huge swaths of data and meaningful conclusions.
AlphaZero, described as“a general reinforcement learning algorithm,” taught itself to play chess, shoji, and Go by playing against itself.
The results of the UAlberta and IBM research demonstrated that even on more challenging neuroimaging data collected from multiple sites(different machines, across differentgroups of subjects etc.), the machine learning algorithm was able to discriminate between patients with schizophrenia and the control group with 74 per cent accuracy using the correlations in activity across different areas of the brain.
The empirical risk minimization principle[1] states that the learning algorithm should choose a hypothesis h^{\displaystyle{\hat{h}}} which minimizes the empirical risk.
MobileODT worked with the National Cancer Institute to develop a machine learning algorithm, called automatic visual evaluation(AVE), that can produce an accurate diagnosis in minutes.
INFINIDAT takes a software approach that uses machine learning algorithms to extract very high performance and seven nines reliability out of low-cost hardware.