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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...

  3. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    e. In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts ...

  4. Linux - Wikipedia

    en.wikipedia.org/wiki/Linux

    On Linux systems using ELF-format executable files, the dynamic linker that manages the use of dynamic libraries is known as ld-linux.so. If the system is set up for the user to compile software themselves, header files will also be included to describe the programming interface of installed libraries.

  5. Résumé - Wikipedia

    en.wikipedia.org/wiki/Résumé

    An example of a résumé with a common format with the name John Doe. [1] A résumé, sometimes spelled resume (or alternatively resumé ), [a] [2] is a document created and used by a person to present their background, skills, and accomplishments. Résumés can be used for a variety of reasons, but most often they are used to secure new ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary field [ 10] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing data ...

  7. FASTQ format - Wikipedia

    en.wikipedia.org/wiki/FASTQ_format

    The FAST4 format was invented as a derivative of the FASTQ format where each of the 4 bases (A,C,G,T) had separate probabilities stored. It was part of the Swift basecaller, an open source package for primary data analysis on next-gen sequence data "from images to basecalls". The FAST5 format was invented as an extension of the FAST4 format.

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