Online or onsite, instructor-led live Mathematica training courses in Recife.
Recife - JCPM Trade Center
60 Eng. Antonio de Goes Avenue, 7º and 14º floor, , Recife, Brazil, 51010-000
The Recife JCPM Trade Center is in a 20-story building. The center has access to a helipad and five floors of parking. It is ...
The Recife JCPM Trade Center is in a 20-story building. The center has access to a helipad and five floors of parking. It is 10km from Guararapas International Airport.
Recife, Cicero Dias - Shopping Center Recife
Rua Padre Carapuceiro, 858 , Recife, Brazil, 51020-280
The business center is located in the Cicero Dias Tower, part of a prestigious complex of five buildings, the Queiroz Galvão...
The business center is located in the Cicero Dias Tower, part of a prestigious complex of five buildings, the Queiroz Galvão Center. Its stands out for its distinctive architecture and for being located in an area with a consolidated entrepreneurial vocation. The business center has a privileged position in Pernambuco, in one of the greatest development axis of northeastern Brazil. The business center is walking distance to one of the Recife's greatest shopping centers and from Shopping subway station. It is also 30 minutes away from the Port of Suape, one of the most important seaports in the country and a 7-minute drive from Guararapes International Airport.
The "Mathematica - wprowadzenie, wizualizacja i prezentacja danych" training is aimed at participants with basic mathematical knowledge. Mathematica, as a powerful mathematical engine, enables effective calculations, creating text documents, building charts and presenting data. Participants will gain practical skills in working with Mathematica, used, among others, in mathematics, physics, biology, financial analysis and other fields.
This instructor-led, live training in Recife (online or onsite) is aimed at data scientists who wish to use machine learning in Mathematica for data analysis.
By the end of this training, participants will be able to:
Build and train machine learning models.
Import and prepare data for machine learning.
Separate training data from test data.
Explore deep learning and neural network applications in data analysis.
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