Machine Learning Applications using Python. Cases Studies from Healthcare, Retail and Finance

Contents......Page 3
Intro......Page 9
ML in Healthcare......Page 11
Installing Python for the Exercises......Page 12
End    Notes......Page 21
Scenario    2025......Page 22
Narrow vs. Broad Machine Learning......Page 23
Current State of Healthcare Institutions  Around the World......Page 25
End    Notes......Page 43
Areas of Healthcare Research Where There is   Huge Potential......Page 45
Common Machine Learning Applications  in Radiology......Page 48
Working with a Healthcare Data Set......Page 49
Implementing a Patient Electronic Health   Record Data Set......Page 52
End    Notes......Page 83
Case Studies in Healthcare AI......Page 84
CASE STUDY 1: Lab Coordinator Problem......Page 85
CASE STUDY 2: Hospital Food Wastage Problem......Page 107
Pitfalls to avoid with ML in Healthcare......Page 127
Meeting the Business Objectives......Page 128
This is Not a Competition, It is Applied Business!......Page 129
Don’t Get Caught in the Planning and Design Flaws......Page 132
Choosing the Best Algorithm for Your Prediction  Model......Page 135
Are You Using Agile Machine Learning?......Page 136
Ascertaining Technical Risks in the Project......Page 137
End    Note......Page 140
Intro-Hospital Communication Apps......Page 141
Connected Patient Data Networks......Page 146
IoT    in Healthcare......Page 148
End    Note......Page 151
ML in Retail......Page 152
Retail    Segments......Page 154
Retail Value Proposition......Page 156
The Process of Technology Adoption in the Retail  Sector......Page 158
The Current State of Analytics in the Retail Sector......Page 160
Scenario    2025......Page 163
Narrow vs Broad Machine Learning in Retail......Page 165
The Current State of Retail Institutions  Around the World......Page 166
Importance of Machine Learning in Retail......Page 168
Data Collection Methods......Page 174
Limitations  of the Study......Page 175
Examining    the Study......Page 176
End    Notes......Page 185
Implement ML in Retail......Page 186
Implementing Machine Learning Life Cycle in Retail......Page 188
End    Notes......Page 219
What Are Recommender Systems?......Page 220
CASE STUDY 1: Recommendation Engine Creation  for Online Retail Mart......Page 221
CASE STUDY 2: Talking Bots for AMDAP Retail Group......Page 236
End    Notes......Page 240
Supply Chain Management and Logistics......Page 241
Inventor  y  Management......Page 243
Customer  Management......Page 244
Internet    of Things......Page 247
End    Note......Page 249
Connected Retail Stores......Page 250
Connected    Warehouses......Page 253
Collaborative Community Mobile Stores......Page 255
End    Notes......Page 258
ML in Finance......Page 259
Financial    Segments......Page 261
Finance Value Proposition......Page 262
The Process of Technology Adoption in the Finance  Sector......Page 265
End    Notes......Page 270
Scenario    2027......Page 271
Narrow vs Broad Machine Learning in Finance......Page 272
Importance of Machine Learning in Finance......Page 274
Research Design Overview......Page 280
Data    Analysis......Page 281
Examining    the Study......Page 282
Phases of Technology Adoption in   Finance, 2018......Page 290
End    Notes......Page 292
Implement ML in Finance......Page 294
Implementing Machine Learning Life Cycle  in Finance......Page 296
End    Note......Page 323
CASE STUDY 1: Stock Market Movement Prediction......Page 324
CASE STUDY 2: Detecting Financial Statements  Fraud......Page 346
End    Notes......Page 353
The Regulatory Pitfall......Page 354
The Data Privacy Pitfall......Page 359
End    Note......Page 361
Connected    Bank......Page 362
Fly-In Financial Markets......Page 366
Financial Asset Exchange......Page 368
End    Note......Page 371
Index......Page 372