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Events

A ‘Machine’ View on the Human Capital Development

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On the 18th of November 2022, a new webinar will be held by the Institute for Statistical Studies and Economics of Knowledge (ISSEK) of the Higher School of Economics at the Human Capital Multidisciplinary Research Centre.

The speaker — HSE ISSEK Centre for Strategic Analysis and Big Data leading expert Mikhail Zakharov — will introduce colleagues’ experience in analyzing large amounts of textual data on inflation, unemployment, investment in education, and other aspects that are significant for studying the factors affecting the human capital development.

Webinar agenda:

With the development of machine learning technologies, the set of methods and the range of their application by the modern expert community become more and more diverse. The speaker will show how machine learning (based on the Transformer model), hyperparameters selection, and data labeling are being actively applied on the example of real projects of the HSE ISSEK Centre for Strategic Analysis and Big Data that are performed using the iFORA system, and how the problem of lack of labeled data is solved.

We invite undergraduate and graduate students, young researchers, and all persons interested in machine learning, big data analytics tools and current human capital agenda.

Time and date: the 18th of November 2022, 4:30 pm (Moscow time)

Meeting format: online, MS Teams platform

To participate, you need to register via the link below.

Contact person: Maria Svarchevskaya (msvarchevskaya@hse.ru)

To register

The webinar is organised within the framework of the world-class Human Capital Multidisciplinary Research Centre at the expense of a research grant funded by the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2022-325).

The participants of the previous webinars were able to get acquainted with the basic approaches to sentiment analysis (the study of data sets to identify public sentiment regarding certain phenomena/technologies / products) and some specific features of working with Chinese-language big data sources.