Приклади вживання In machine learning Англійська мовою та їх переклад на Українською
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We are actively engaged in machine learning and blockchain technologies as part of the team's internal projects.
neural network function in machine learning has long been able to learn various skills virtually unaided.
Many scientists are arguing that the latest techniques in machine learning and AI represent a fundamentally new way of doing scientific research.
But back in Version 10 we also made a great step forward in machine learning- developing extremely automated core functions(Classify and Predict) for learning by example.
With advances in machine learning, we have now built systems that block millions of fake accounts every day.
Developers have an experience in machine learning, and a team consists of industry experts.
This includes typing in machine learning and tips on choosing the right software package for data analysis.
Interest in machine learning has exploded in recent years as companies realize it has applications in photography,
Mutual information has been used as a criterion for feature selection and feature transformations in machine learning.
Today, SVM is one of the most frequently used algorithms in machine learning, which is used in many practical applications, including medical diagnosis and weather forecasting.
These systems are one of the most important tools used in machine learning, and they are especially good at detecting patterns, which a biological brain finds it too difficult to process.
including the development of a course in machine learning for the well-known educational platform Coursera.
much simpler methods such as linear classifiers gradually overtook neural networks in machine learning popularity.
advanced methods in machine learning, as well as their underlying theory.
His work led to the development of the boosting ensemble algorithm used in machine learning.
In machine learning, the environment is formulated as a Markov decision process(MDP),
The second method optimised scores through gradient descent- a mathematical technique commonly used in machine learning for making small,
question of Kearns and Valiant has had significant ramifications in machine learning and statistics, most notably leading to the development of boosting.
that people interested in machine learning rarely leave.
Exciting developments in machine learning, sensor technology,