- Implicit parallelism: If you want to execute a loop sequentially you have to explicitly write that. The big claim is of course, using this efficiently on multi-core machines.
- Support for unicode: As a result, the scientific research community can make use of greek alphabets in their code, and even use things like superscripts, subscripts, and hats and bars! This means that your code is going to look a lot more like your algorithm.
- Automated Type inference: The system has extensive type inference (the kind that functional languages and C# 3.0 have) and that means that your code is far more readable.
- Extensive library support: In fact, even some parts of the main system are implemented as libraries. They expose the parsed AST to the programmer, and give him extensive control.
Infinitely scalable machine learning with Amazon SageMaker - In machine learning, more is usually more. For example, training on more data means more accurate models. At AWS, we continue to strive to enable builder...
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