Examples of using Machine learning algorithms in English and their translations into Greek
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We also power our ads with machine learning algorithms.
Using machine learning algorithms in order to build computer vision applications.
Often, these measures are multi-dimensional,so traditional Machine Learning algorithms cannot handle them directly.
Using machine learning algorithms in order to build computer vision applications.
In reality, today's AI algorithms are nothing more than traditional machine learning algorithms.
Machine learning algorithms are used throughout the process and improve over time.
We processed all the available data and allowed machine learning algorithms to decide which criteria are truly important.
Machine learning algorithms can calculate detriment using satellite images or drones to explore fields.
A few years later, Geoffrey Hinton, already renowned for his work on artificial neural networks,designed machine learning algorithms.
They then used machine learning algorithms to classify the patients into one of the three groups.
As it turns out, computers are rapidly getting better at image recognition thanks to machine learning algorithms, such as neural networks.
Weka is a collection of machine learning algorithms for solving real-world data mining problems.
Utilize basic building blocks, general principles and cloud technologies such as Amazon Web Services(AWS)to design machine learning algorithms.
Machine learning algorithms can be organized into a taxonomy based on the desired outcome of the algorithm. .
The course teaches statistics for business analysis, machine learning algorithms, deep learning with TensorFlow, and programming with Python.
New machine learning algorithms that can now find five times more non-brand-safe videos than before.
For this purpose, various techniques have been developed, utilizing machine learning algorithms for the segmentation, recognition and classification of sound events.
Machine learning algorithms have already surpassed humans by recognizing ordinary conversational speech, as the results of a Microsoft software suggest.
Computational and performance analysis of machine learning algorithms is a branch of statistics known as computational theory of learning. .
Machine learning algorithms are often re-trained on data collected during operation to adapt to changes in the underlying data distribution.
And these things only work if there's anenormous amount of data, so they also encourage deep surveillance on all of us so that the machine learning algorithms can work.
The results showed that machine learning algorithms can tell the differences between the groups with up to 93 percent accuracy.
Together with the wide adoption of multi-core architectures, as well as in-memory databases,this has paved the way for extremely efficient implementations of machine learning algorithms.
The results showed that machine learning algorithms can tell the differences between the groups with up to 93 per cent accuracy.
GBDX, a powerful, cloud-based tool with access to DigitalGlobe's 100 petabyte imagery archive,can harness machine learning algorithms to revolutionize traditional 3D production models.
There is no point implementing machine learning algorithms or neural networks for an IoT initiative unless it is absolutely necessary.
Leo Breiman distinguished two statistical modelling paradigms: data model and algorithmic model,[15]wherein'algorithmic model' means more or less the machine learning algorithms like Random forest.
The project is based on machine learning algorithms and astronomical detection tools developed through the open source software, Astropy.
Google's search engine, face recognition on smartphones, self-driving cars, Netflix andSpotify recommendation systems all use machine learning algorithms to adapt to the individual user.
Is engine uses machine learning algorithms to interpret the data matrix built by the comments and people reactions in real-time.