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Time series analysis involves identifying attributes of your time series data, such as trend and seasonality, by measuring statistical properties.
High-performance computing projects require massive quantities of compute resources. Pairing simulation and specialized hardware with the cloud powers the breakthroughs of the future.
An open, services-oriented approach has clear advantages for building modular and scalable applications. We should take the same approach to our data.
Appen survey of business leaders and data scientists indicates that AI initiatives are delivering business value but challenges still exist.
Visualizing time series data is often the first step in observing trends that can guide time series modeling and analysis.
Want faster number-crunching in Python? You can speed up your existing Python code with the Numba JIT, often with only one instruction.
Microsoft is wrapping its Cognitive Services machine learning platform as business-focused services.
With every organization generating and accessing multiple data sources, an integration platform ensures every team has the data they need to drive the business forward.
If the ubiquitous spreadsheet program is the gateway to data science, Python aims to be the next step.
Making great efforts to tout its closed source software, Snowflake may be trying to convince an audience that doesn't really care.