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Comparison and Relationship between Big data Analytics and Machine learning

EasyChair Preprint no. 2143

8 pagesDate: December 12, 2019


Big data is a term that applies to large objects of data that vary in  nature whether they are structure , unstructured or semi- structured, including from internal or external sources of the organization, and are generated with a high degree of speed with a  turbulent model, which does not Fully compatible with traditional and structured data warehouses and requiring a robust and complex ecosystem with a high-performance computing platform

and analytical capabilities to capture, process, transform, detect, extract and derive value and deep insights within a timed time. Machine learning is a type of Artificial Intelligence, which allows software applications to become more accurate in predicting results without explicitly programming them. The primary focus of machine learning is to build algorithms that can receive input data and use statistical analysis to predict outputs within an acceptable range. In this paper we will introduce the concept of big data and machine learning and the comparison between them and the techniques used for both and finally we will see the relationship between them

Keyphrases: Big Data, deep learning, machine learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Mohammed Abdelmoneim and Saad Subair},
  title = {Comparison and Relationship between Big data Analytics and Machine learning},
  howpublished = {EasyChair Preprint no. 2143},

  year = {EasyChair, 2019}}
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