title: So Much Data So Little Math: How to Predict Data Trends -- 5 Easy Profitable Methods
author:  William D. May 
description: <b>William D. May</b> is a Senior Scientist with the Central Intelligence Agency and an Adjunct Professor of Computer Science at Virginia Tech.
zlib_text: The Big Book of Data  
  Science Use Cases
  A collection of technical blogs, including code 
  samples and notebooks
  
  Contents
  T H E  B I G  B O O K  O F  D AT A  S C I E N C E  U S E  C A S E S
  CHAPTER 1: Introduction 
  3
  CHAPTER 2: Democratizing Financial Time Series Analysis  
  4
  CHAPTER 3:	 	Using	Dynamic	Time	Warping	and	MLflow	to	Detect	Sales	Trends	Series	
   
  PART 1 :  Understanding Dynamic Time Warping 
  13
   
  PART 2: Using	Dynamic	Time	Warping	and	MLflow	to	Detect	Sales	Trends	
  19	
  CHAPTER 4:  How	a	Fresh	Approach	to	Safety	Stock	Analysis	Can	Optimize	Inventory	
  26
  CHAPTER 5:	 	New	Methods	for	Improving	Supply	Chain	Demand	Forecasting	
  31
  CHAPTER 6: Fine-Grained Time Series Forecasting at Scale With Prophet and Apache Spark  
  40
  CHAPTER 7: 	Detecting	Financial	Fraud	at	Scale	With	Decision	Trees	and	MLflow	on	Databricks	
  48	
  CHAPTER 8:	 	How	Virgin	Hyperloop	One	Reduced	Processing	Time	From	
  57 
  Hours to Minutes With Koalas 
  CHAPTER 9:	 Delivering	a	Personalized	Shopping	Experience	With	