Machine Learning and AI Integration in Databricks for Big Data

Ravi Shankar Koppula

Abstract: This paper explores the integration of machine learning (ML) and artificial intelligence (AI) within the Databricks platform, emphasizing its capabilities for big data analytics. Databricks, built on Apache Spark, provides a unified analytics environment that supports data science collaboration through interactive notebooks and scalable processing. The paper discusses the foundational concepts of machine learning and AI, the significance of data preparation, and the utilization of ML libraries such as MLLib and H2O within Databricks. Advanced techniques including deep learning and neural networks are examined, highlighting their practical applications in real-world scenarios. The integration of Databricks' tools with machine learning frameworks enables efficient data engineering and model deployment, offering a robust solution for enterprises to leverage big data for predictive analytics and decision-making.

Keywords: Databricks, Apache Spark, Machine Learning (ML), Artificial Intelligence (AI), Big Data, Data Preparation, MLLib, H2O, Deep Learning, Neural Networks

How to Cite?: Ravi Shankar Koppula, "Machine Learning and AI Integration in Databricks for Big Data", Volume 12 Issue 2, February 2023, International Journal of Science and Research (IJSR), Pages: 1754-1758, https://www.ijsr.net/getabstract.php?paperid=SR24819211633, DOI: https://dx.doi.org/10.21275/SR24819211633