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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

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

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

    List of GitHub repositories of the project: IBM This data is not pre-processed List of GitHub repositories of the project: IBM Cloud This data is not pre-processed List of GitHub repositories of the project: Build Lab Team This data is not pre-processed List of GitHub repositories of the project: Terraform IBM Modules This data is not pre-processed

  4. pandas (software) - Wikipedia

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

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.

  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. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Then, analyze the source data to determine the most appropriate data and model building approach (models are only as useful as the applicable data used to build them). Select and transform the data in order to create models. Create and test models in order to evaluate if they are valid and will be able to meet project goals and metrics.

  7. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.

  8. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

  9. Biopython - Wikipedia

    en.wikipedia.org/wiki/Biopython

    The Biopython project is an open-source collection of non-commercial Python tools for computational biology and bioinformatics, created by an international association of developers. [ 1 ] [ 4 ] [ 5 ] It contains classes to represent biological sequences and sequence annotations , and it is able to read and write to a variety of file formats.