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  2. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  3. API testing - Wikipedia

    en.wikipedia.org/wiki/Api_testing

    API testing is a type of software testing that involves testing application programming interfaces (APIs) directly and as part of integration testing to determine if they meet expectations for functionality, reliability, performance, and security. [1]

  4. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]

  5. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  6. LoadRunner - Wikipedia

    en.wikipedia.org/wiki/LoadRunner

    LoadRunner is a software testing tool from OpenText.It is used to test applications, measuring system behavior and performance under load.. LoadRunner can simulate millions of users concurrently using application software, recording and later analyzing the performance of key components of the application whilst under load.

  7. Model-based testing - Wikipedia

    en.wikipedia.org/wiki/Model-based_testing

    General model-based testing setting. Model-based testing is an application of model-based design for designing and optionally also executing artifacts to perform software testing or system testing. Models can be used to represent the desired behavior of a system under test (SUT), or to represent testing strategies and a test environment. The ...

  8. C Sharp syntax - Wikipedia

    en.wikipedia.org/wiki/C_Sharp_syntax

    C# 3.0 introduced type inference, allowing the type specifier of a variable declaration to be replaced by the keyword var, if its actual type can be statically determined from the initializer. This reduces repetition, especially for types with multiple generic type-parameters , and adheres more closely to the DRY principle.

  9. Ford Proving Grounds - Wikipedia

    en.wikipedia.org/wiki/Ford_Proving_Grounds

    Stats: 796 acres (3.22 km 2), 49.7 miles (80.0 km) of roads; Major facilities: Humidity chambers, salt water/mud baths, straightaway, high speed track, durability road, special surfaces, side wind facility; Major testing: Car and light truck durability; performance, ride, and handling