Monster.ca

Ingénieur en vision par ordinateur

Responsable de science des données

Ingénieur logiciel en robotique

A Computer Scientist conducts research and studies complex problems in computing. Develops computer algorithms that provide the foundation for advances in technology. May study computer hardware architecture, robotics or software, and collaborate with electrical engineers and other computer professionals.

Scientifique de données

Développeur/ingénieur logiciel

Architecte logiciel (général)

Développeur de jeux vidéos

Ingénieur en solutions

Informaticien

Transfer learning (TL) is a research problem in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks. This area of research bears some relation to the long history of psychological literature on transfer of learning, although practical ties between the two fields are limited. From the practical standpoint, reusing or transferring information from previously learned tasks for the learning of new tasks has the potential to significantly improve the sample efficiency of a reinforcement learning agent.

Transfer Learning

Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem.

Natural Language Understanding

spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.

SpaCy (NLP Software)

Bidirectional Encoder Representations from Transformers (BERT) is a transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google. BERT was created and published in 2018 by Jacob Devlin and his colleagues from Google. In 2019, Google announced that it had begun leveraging BERT in its search engine, and by late 2020 it was using BERT in almost every English-language query. A 2020 literature survey concluded that "in a little over a year, BERT has become a ubiquitous baseline in NLP experiments", counting over 150 research publications analyzing and improving the model.

BERT (NLP Model)

Hugging Face (NLP Framework)

Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

Location	Salaire médian
Calgary, AB	$88,832
National	$88,832
Emplacement +/-	0% Supérieur
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Location	Salaire médian
Calgary, AB	$88,832
National	$88,832
Emplacement +/-	0% Supérieur
	Faites une autre recherche
	Montrez-moi les emplois associés

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