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  2. 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 ...

  3. Iris flower data set - Wikipedia

    en.wikipedia.org/wiki/Iris_flower_data_set

    The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]

  4. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Car Evaluation Data Set Car properties and their overall acceptability. Six categorical features given. 1728 Text Classification 1997 [13] [14] M. Bohanec YouTube Comedy Slam Preference Dataset User vote data for pairs of videos shown on YouTube. Users voted on funnier videos. Video metadata given. 1,138,562 Text Classification 2012 [15] [16 ...

  5. Orange (software) - Wikipedia

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

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.

  6. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    ML involves the study and construction of algorithms that can learn from and make predictions on data. [3] These algorithms operate by building a model from a training set of example observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.

  7. What Is Corn Syrup? Here’s Why You Should Always Have This ...

    www.aol.com/corn-syrup-why-always-staple...

    How to use corn syrup. Corn syrup is a baker’s secret weapon. It prevents sugar from crystallizing (or lumps from forming). It’s a common ingredient in caramel sauce and recipes that use a hot ...

  8. Food poisoning is extremely common. But that doesn't ... - AOL

    www.aol.com/food-poisoning-extremely-common...

    Few things will put a damper on your vacation or holiday faster than food poisoning.The intense stomach pain, rushing to the toilet and feeling relegated to bed keeps just about everyone out of ...

  9. 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]