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  Published Paper Details:

  Paper Title

Advancements in AI, Machine Learning and Big Data Engineering: A Comprehensive Review and Future Directions

  Authors

  Ekta Chandak,  Tanushree Parmar

  Keywords

Data Governance, Anomaly Detection, AI Systems

  Abstract


Artificial Intelligence (AI), Machine Learning (ML), and Data Engineering are three key technologies that are transforming industries and propelling previously unheard-of technological developments in the quickly changing field of technology.The management should take initiatives to make students ready for the industry exposure,how to use Artificial Intelligence(AI) in business process,study materials. In order to fully utilize the potential of large datasets, this research investigates the connections and synergies between these three fields. The basics of artificial intelligence (AI) are covered in the first section, along with how intelligent computers mimic human cognitive processes. It highlights the importance of algorithms in decision-making and problem-solving while discussing the revolutionary effects of AI in a variety of industries, including healthcare and finance. The author has tried to discuss in this study how to implement AI, ML and Big Data Engineering in the industry , how it can be useful in different sectors, and in their placement drives as well, the employability related to AI,ML and Big Data Engineering .

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2403340

  Paper ID - 252831

  Page Number(s) - c732-c745

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Ekta Chandak,  Tanushree Parmar,   "Advancements in AI, Machine Learning and Big Data Engineering: A Comprehensive Review and Future Directions", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.c732-c745, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT2403340.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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