Mar 22, 2023 · This paper begins by providing an overview of machine learning and deep learning algorithms. The research then moves on to machine learning problems and challenges, as well as...

May 10, 2017 · Big data enables ML algorithms to uncover more fine-grained patterns and make more timely and accurate predictions than ever before; on the other hand, it presents major challenges to ML such as model scalability and distributed computing.

Apr 20, 2017 · Consequently, this paper compiles, summarizes, and organizes machine learning challenges with Big Data. In contrast to other research that discusses challenges, this work highlights the cause–effect relationship by organizing challenges according to Big Data Vs or dimensions that instigated the issue: volume, velocity, variety, or veracity.

Jan 27, 2022 · The study outcome shows that deep neural networks (15%), support vector machines (15%), artificial neural networks (14%), decision trees (12%), and ensemble learning techniques (11%) are widely...

Jan 16, 2025 · Although big data is a breakthrough for organisations, there are several challenges for companies to face. Implementing big data solutions requires specialised skills in data engineering, data science, and machine learning.

Oct 10, 2024 · Let’s have a look. 1. Poor Quality of Data Data plays a significant role in the machine learning process. One of the significant issues that machine learning professionals face is the absence of good quality data. Unclean and noisy data can make the whole process extremely exhausting.

Dec 15, 2020 · This book is intended to present the state of the art in research on machine learning and big data analytics.

Aug 2, 2023 · Yet, enterprises face numerous challenges of big data analytics while integrating such tools into their digital infrastructures and data workflows. In this article, you will discover how to implement big data analytics and derive smart insights from all types of data, minimizing failure and financial loss risks.

This paper begins by providing an overview of machine learning and deep learning algorithms. The research then moves on to machine learning problems and challenges, as well as potential solutions. The investigation into deep learning principles of big data continues after that.

Feb 18, 2025 · Despite the challenges in machine learning adoption, businesses can successfully integrate ML by addressing data quality issues, bridging talent gaps, optimizing costs, ensuring seamless integration, and adhering to ethical guidelines.