-
Previous Article
Older adults, frailty, and the social and behavioral determinants of health
- BDIA Home
- This Issue
-
Next Article
An application of PART to the Football Manager data for players clusters analyses to inform club team formation
doi: 10.3934/bdia.2018001
Understanding AI in a world of big data
Environics Analytics, 33 Bloor St. East, Toronto, Ont. M4W3H1, Canada |
Big Data and AI are now very popular concepts within the public lexicon. Yet, much confusion exists as to what these concepts actually mean and more importantly why they are significant forces within the world today. New tools and technologies now allow better access as well as facilitating the analysis of this data for better decision-making. But the discipline of data science with its four-step process in conducting any analysis is the key towards success in both non-advanced and advanced analytics which would, of course, include the use of AI. This paper attempts to demystify these concepts from a data science perspective. In attempting to understand Big Data and AI, we look at the history of data science and how these more recent concepts have helped to optimize solutions within this 4 step process.
Mathematics Subject Classification:
91C20, 62F07.
Citation:
Richard Boire.
Understanding AI in a world of big data. Big Data & Information Analytics, doi: 10.3934/bdia.2018001
![]()
References:
show all references
References:
Figure 4.
Example of Structured Data
Figure 5.
Example of Twitter Data
Figure 6.
Sequential vs. Parallel Data Processing
Figure 7.
Schematic of Simple Neural Net-One Hidden layer
Figure 10.
Examples of Neural Nets
Figure 11.
Sample of 3 records
Figure 12.
Sample of 3 records-Fixed
Figure 13.
Frequency Distribution of Numeric Variable
Figure 14.
Frequency Distribution of Character Variable
Figure 15.
Example of Data Diagnostics
Figure 16.
Example of Alteryx Software
Figure 17.
Example of Gains/Decile Table
Figure 18.
Example of Final Model Variable Contribution Report
Figure 19.
Example of Final Model Variable Contribution Report
| [1] |
Yang Yu. Introduction: Special issue on computational intelligence methods for big data and information analytics. Big Data & Information Analytics, 2017, 2 (1) : i-ii. doi: 10.3934/bdia.201701i |
| [2] |
Yaguang Huangfu, Guanqing Liang, Jiannong Cao. MatrixMap: Programming abstraction and implementation of matrix computation for big data analytics. Big Data & Information Analytics, 2016, 1 (4) : 349-376. doi: 10.3934/bdia.2016015 |
| [3] |
Xiangmin Zhang. User perceived learning from interactive searching on big medical literature data. Big Data & Information Analytics, 2017, 2 (5) : 1-16. doi: 10.3934/bdia.2017019 |
| [4] |
Tieliang Gong, Qian Zhao, Deyu Meng, Zongben Xu. Why curriculum learning & self-paced learning work in big/noisy data: A theoretical perspective. Big Data & Information Analytics, 2016, 1 (1) : 111-127. doi: 10.3934/bdia.2016.1.111 |
| [5] |
Jiang Xie, Junfu Xu, Celine Nie, Qing Nie. Machine learning of swimming data via wisdom of crowd and regression analysis. Mathematical Biosciences & Engineering, 2017, 14 (2) : 511-527. doi: 10.3934/mbe.2017031 |
| [6] |
Nick Cercone, F'IEEE. What's the big deal about big data?. Big Data & Information Analytics, 2016, 1 (1) : 31-79. doi: 10.3934/bdia.2016.1.31 |
| [7] |
James H. Elder. A new training program in data analytics & visualization. Big Data & Information Analytics, 2016, 1 (1) : i-iii. doi: 10.3934/bdia.2016.1.1i |
| [8] |
Pankaj Sharma, David Baglee, Jaime Campos, Erkki Jantunen. Big data collection and analysis for manufacturing organisations. Big Data & Information Analytics, 2017, 2 (2) : 127-139. doi: 10.3934/bdia.2017002 |
| [9] |
Enrico Capobianco. Born to be big: Data, graphs, and their entangled complexity. Big Data & Information Analytics, 2016, 1 (2&3) : 163-169. doi: 10.3934/bdia.2016002 |
| [10] |
Ali Asgary, Jianhong Wu. ADERSIM-IBM partnership in big data. Big Data & Information Analytics, 2016, 1 (4) : 277-278. doi: 10.3934/bdia.2016010 |
| [11] |
Weidong Bao, Wenhua Xiao, Haoran Ji, Chao Chen, Xiaomin Zhu, Jianhong Wu. Towards big data processing in clouds: An online cost-minimization approach. Big Data & Information Analytics, 2016, 1 (1) : 15-29. doi: 10.3934/bdia.2016.1.15 |
| [12] |
Roya Soltani, Seyed Jafar Sadjadi, Mona Rahnama. Artificial intelligence combined with nonlinear optimization techniques and their application for yield curve optimization. Journal of Industrial & Management Optimization, 2017, 13 (4) : 1701-1721. doi: 10.3934/jimo.2017014 |
| [13] |
Luís Tiago Paiva, Fernando A. C. C. Fontes. Sampled–data model predictive control: Adaptive time–mesh refinement algorithms and guarantees of stability. Discrete & Continuous Dynamical Systems - B, 2019, 24 (5) : 2335-2364. doi: 10.3934/dcdsb.2019098 |
| [14] |
Jian-Wu Xue, Xiao-Kun Xu, Feng Zhang. Big data dynamic compressive sensing system architecture and optimization algorithm for internet of things. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1401-1414. doi: 10.3934/dcdss.2015.8.1401 |
| [15] |
Liqiang Zhu, Ying-Cheng Lai, Frank C. Hoppensteadt, Jiping He. Characterization of Neural Interaction During Learning and Adaptation from Spike-Train Data. Mathematical Biosciences & Engineering, 2005, 2 (1) : 1-23. doi: 10.3934/mbe.2005.2.1 |
| [16] |
Mingbao Cheng, Shuxian Xiao, Guosheng Liu. Single-machine rescheduling problems with learning effect under disruptions. Journal of Industrial & Management Optimization, 2018, 14 (3) : 967-980. doi: 10.3934/jimo.2017085 |
| [17] |
Stefano Galatolo. Orbit complexity and data compression. Discrete & Continuous Dynamical Systems - A, 2001, 7 (3) : 477-486. doi: 10.3934/dcds.2001.7.477 |
| [18] |
Subrata Dasgupta. Disentangling data, information and knowledge. Big Data & Information Analytics, 2016, 1 (4) : 377-389. doi: 10.3934/bdia.2016016 |
| [19] |
Alessia Marigo. Equilibria for data networks. Networks & Heterogeneous Media, 2007, 2 (3) : 497-528. doi: 10.3934/nhm.2007.2.497 |
| [20] |
Cai-Tong Yue, Jing Liang, Bo-Fei Lang, Bo-Yang Qu. Two-hidden-layer extreme learning machine based wrist vein recognition system. Big Data & Information Analytics, 2017, 2 (1) : 59-68. doi: 10.3934/bdia.2017008 |
Impact Factor:
Tools
Article outline
Figures and Tables
[Back to Top]