Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars.
Informações sobre o curso
HSE University is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
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Principais avaliações do DEEP LEARNING IN COMPUTER VISION
The course assignments are not updated. Many libraries have updated and so have their syntax. And its nightmare getting the exact working version of those libraries. Otherwise the course is good.
Some lectures aren't clearly structured. The homework assignments have downstream dependencies (week 5 depends on earlier weeks) which is not the best format IMO.
The content of the course is exciting. However, the lecturers should provide more reading materials, and update the outdated code in the assignments.
Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.
Sobre Programa de cursos integrados Aprendizagem de máquina avançada
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.
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