Big Data and AI Strategies J.P.Morgan

秋云飞

Table of Contents
I: INTRODUCTION AND OVERVIEW ....................................... 6
Summary ...................................................................................................................... 7
Introduction to Big Data and Machine Learning ......................................................... 9
Classification of Alternative Data Sets ...................................................................... 12
Classification of Machine Learning Techniques ........................................................ 16
Positioning within the Big Data Landscape ............................................................... 21
II: BIG AND ALTERNATIVE DATA ........................................ 25
Overview of Alternative Data .................................................................................... 26
Data from Individual Activity .................................................................................... 30
Data from Business Processes.................................................................................... 38
Data from Sensors ...................................................................................................... 42
III: MACHINE LEARNING METHODS .................................... 51
Overview of Machine Learning Methods .................................................................. 52
Supervised Learning: Regressions ............................................................................. 57
Supervised Learning: Classifications ......................................................................... 77
Unsupervised Learning: Clustering and Factor Analyses .......................................... 93
Deep and Reinforcement Learning .......................................................................... 102
Comparison of Machine Learning Algorithms ........................................................ 117
IV: HANDBOOK OF ALTERNATIVE DATA ......................... 135
Table of contents of data providers .......................................................................... 136
A. Data from Individual Activity ............................................................................. 137
B. Data from Business Processes ............................................................................. 147
C. Data from Sensors ............................................................................................... 176
D. Data Aggregators ................................................................................................ 189
E. Technology Solutions .......................................................................................... 191
APPENDIX ............................................................................. 214
Techniques for Data Collection from Websites ....................................................... 215
Packages and Codes for Machine Learning ............................................................. 226
Mathematical Appendices ........................................................................................ 231
References ................................................................................................................ 254
Glossary ................................................................................................................... 270