Online or onsite, instructor-led live Mathematica training courses in Orleans.
Orléans, Central Station
NobleProg Orléans, 43 Avenue de Paris, Orléans, france, 45000
La Factory offers renovated offices in the heart of the city of Orléans, near the Central Station. Train, tram, buses, and s...
La Factory offers renovated offices in the heart of the city of Orléans, near the Central Station. Train, tram, buses, and shops are near the building (with elevator). There are 300 m² of offices, Factory offers shared offices and individual offices for 1 to 5 people, equipped or not. The offices are very bright (natural light), and have just been renovated in a "design spirit". Services include ADSL Internet via wifi, a large meeting room. All charges are included: electricity, heating, internet, common areas. It is possible to obtain many additional services: direct debit, telephone line, parking, access 24/24 and 7/7 days ... La Factory is also a service for direct debit and rental of the meeting room for external companies Nonresidents. The meeting room (32 m² / 12 seats), like the other offices, has just been renovated. Services include ADSL Internet via wifi and other charges (electricity, heating, cleaning). Many services are also available, on demand: video projector, coffee machine with pods, tea, chocolate, catering service, drinks, conference call service.
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 Orleans (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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