Summary: This is a discussion of social injustice, real or perceived, promulgated or perpetuated by machine learning models. We propose a simple solution based on wide spread misunderstanding of what ML models can do.
Added by William Vorhies on September 11, 2020 at 1:38pm — No Comments
Summary: A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing.
Our profession of…Continue
Added by William Vorhies on December 4, 2019 at 3:12pm — No Comments
Summary: True prescriptive analytics requires the use of real optimization techniques that very few applications actually use. Here’s a refresher on optimization with examples of where and how they’re best used.
Summary: Which is more important, the data or the algorithms? This chicken and egg question led me to realize that it’s the data, and specifically the way we store and process the data that has dominated data science over the last 10 years. And it all leads back to Hadoop.
Summary: A year ago we wrote about the emergence of fully automated predictive analytic platforms including some with true One-Click Data-In Model-Out capability. We revisited the five contenders from last year with one new addition and found the automation movement continues to move forward. We also observed some players from last year have now gone in different directions. …Continue
Summary: Quantum computing is already being used in deep learning and promises dramatic reductions in processing time and resource utilization to train even the most complex models. Here are a few things you need to know.
Added by William Vorhies on June 13, 2017 at 8:00am — No Comments
Summary: Someone had to say it. In my opinion R is not the best way to learn data science and not the best way to practice it either. More and more large employers agree.
Summary: Count yourself lucky if you’re not in one of the regulated industries where regulation requires you to value interpretability over accuracy. This has been a serious financial weight on the economy but innovations in Deep Learning point a way out.
As Data Scientists we tend to take as gospel that more accuracy is better. There…Continue
Added by William Vorhies on February 28, 2017 at 9:21am — No Comments
Summary: To ensure quality in your data science group, make sure you’re enforcing a standard methodology. This includes not only traditional data analytic projects but also our most advanced recommenders, text, image, and language processing, deep learning, and AI projects.
A Little HistoryContinue
Summary: Will Automated Predictive Analytics be a boon to professional data scientists or a dangerous diversion allowing well-meaning, motivated but amateur users try to implement predictive analytics. More on the conversation started last week about new One-Click Data-In Model-Out platforms.
I have always been very much…Continue
Summary: At least one instance of Real Time Predictive Model development in a streaming data problem has been shown to be more accurate than its batch counterpart. Whether this can be generalized is still an open question. It does challenge the assumption that Time-to-Insight can never be real time.
A few months back I was making my way through the latest literature on “real time analytics” and “in stream analytics” and my blood pressure was rising. …Continue
This is a continuation of the ‘how to become a data scientist conversation’ (see “So You Want to be a Data Scientist” at…Continue
Summary: Is the addition of “Prescriptive” analytics to our nomenclature really worthwhile or are we just confusing our customers?
I admit to being annoyed when this or that industry wag tries to coin a new term to describe some portion of the discipline we are already practicing. Some of these folks I think are…Continue
This article was first posted in 2014 but the message bears repeating. There is a lot being written about tools simple enough for the citizen data scientist to operate. The unstated constraint is that if you don't have significant experience in data science then these will always be "good enough" models. The problem is that 'good enough' models under achieve both revenue and profit. Very small increases in model fitness can translate into much larger increases in campaign ROI. Business…Continue
Before we get to the…Continue
Added by William Vorhies on September 5, 2014 at 8:30am — No Comments
Summary: This blog series is designed to help you understand which NOSQL Big Data database is right for you. It is addressed to business executives and managers who need a primer on how this decision should be made.
Starting a Big Data Initiative is…Continue
Summary: Gartner says that predictive analytics is a mature technology yet only one company in eight is currently utilizing this ability to predict the future of sales, finance, production, and virtually every other area of the enterprise. What’s holding them back?
In an earlier posting we argued that much of what is holding companies back from…Continue
Summary: Gartner says that predictive analytics is a mature technology yet only one company in eight is currently utilizing this ability to predict the future of sales, finance, production, and virtually every other area of the…Continue
Added by William Vorhies on August 13, 2014 at 10:54am — No Comments