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  2. PsychoPy - Wikipedia

    en.wikipedia.org/wiki/PsychoPy

    PsychoPy is an open source software package written in the Python programming language primarily for use in neuroscience and experimental psychology research. [ 2 ] [ 3 ] Developed initially as a Python library and then as an application with a graphical interface , it now also supports JavaScript outputs to run studies online and on mobile ...

  3. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Python is a high-level, general-purpose programming language that is popular in artificial intelligence. [1] It has a simple, flexible and easily readable syntax. [2] Its popularity results in a vast ecosystem of libraries, including for deep learning, such as PyTorch, TensorFlow, Keras, Google JAX.

  4. List of open-source bioinformatics software - Wikipedia

    en.wikipedia.org/wiki/List_of_open-source...

    Apache 2.0 Maastricht University: Orange: Component-based data mining and machine learning software suite written in C++, featuring a visual programming front-end for exploratory data analysis and interactive visualization, and Python bindings and libraries for scripting Linux, macOS, Windows: GPL: University of Ljubljana: SAMtools

  5. Jenkins hash function - Wikipedia

    en.wikipedia.org/wiki/Jenkins_hash_function

    The lookup3 function consumes input in 12 byte (96 bit) chunks. [9] It may be appropriate when speed is more important than simplicity. Note, though, that any speed improvement from the use of this hash is only likely to be useful for large keys, and that the increased complexity may also have speed consequences such as preventing an optimizing compiler from inlining the hash function.

  6. Profiling (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Profiling_(computer...

    A profiler can be applied to an individual method or at the scale of a module or program, to identify performance bottlenecks by making long-running code obvious. [1] A profiler can be used to understand code from a timing point of view, with the objective of optimizing it to handle various runtime conditions [2] or various loads. [3]

  7. Mixed-data sampling - Wikipedia

    en.wikipedia.org/wiki/Mixed-data_sampling

    The MIDAS can also be used for machine learning time series and panel data nowcasting. [6] [7] The machine learning MIDAS regressions involve Legendre polynomials.High-dimensional mixed frequency time series regressions involve certain data structures that once taken into account should improve the performance of unrestricted estimators in small samples.

  8. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  9. DEAP (software) - Wikipedia

    en.wikipedia.org/wiki/DEAP_(software)

    Distributed Evolutionary Algorithms in Python (DEAP) is an evolutionary computation framework for rapid prototyping and testing of ideas. [2] [3] [4] It incorporates the data structures and tools required to implement most common evolutionary computation techniques such as genetic algorithm, genetic programming, evolution strategies, particle swarm optimization, differential evolution, traffic ...