Online or onsite, instructor-led live Mathematica training courses in Nova Scotia.
Halifax - Purdy Wharf
1959 Upper Water Street, Halifax, Canada, B3J 3N2
Short walk from Scotia Square Mall, next door to the Casino Nova Scotia. 2 blocks from the ferry terminal, building has ...
Short walk from Scotia Square Mall, next door to the Casino Nova Scotia. 2 blocks from the ferry terminal, building has a bus stop right outside, 3 blocks from Citadel Hill Historic Site and Halifax City Hall.
Dartmouth - Metropolitan Place
99 Wyse Road, Dartmouth, Canada, B3A 4S5
Metropolitan Place is an ocean-front building, close to Alderney Landing and home to leading businesses. Motorway exits and ...
Metropolitan Place is an ocean-front building, close to Alderney Landing and home to leading businesses. Motorway exits and the local ferry terminal are located close by, and restaurants cafes are easily accessible for lunch.
Truro - Commercial Street
1 Commercial St., Truro, Canada, B2N 3H8
Build your business with a flexible office space in Truro, the Hub of Nova Scotia. Commute easily to this ideal location usin...
Build your business with a flexible office space in Truro, the Hub of Nova Scotia. Commute easily to this ideal location using the nearby Truro Station, and if you’re driving, Trunk 2 and Trunk 4 highways intersect in the town.
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 Nova Scotia (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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