“If (there) was one thing all people took for granted, (it) was conviction that if you feed honest figures into a computer, honest figures (will) come out. Never doubted it myself till I met a computer with a sense of humor.”
― Robert A. Heinlein, The Moon is a Harsh Mistress
This post is the first in a series of articles in which we will explain what Machine Learning is. You don’t have to have formal training or…Continue
In this blog post, I will discuss feature engineering using the Tidyverse collection of libraries. Feature engineering is crucial for a variety of reasons, and it requires some care to produce any useful outcome. In this post, I will consider a dataset that contains description of crimes in San Francisco between…Continue
Added by Burak Himmetoglu on April 10, 2017 at 7:30am — No Comments
Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .
“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?
I have often used this diagram to crisply define IoT.…Continue
(Photo credit: Rob Lavinsky, iRocks.com – CC-BY-SA-3.0)
In 1945, Count ,Richard Taaffe* a Dublin gem collector, was sorting through a set of spinel gems that he had bought, and found one…Continue
Added by Peter Bruce on March 30, 2017 at 2:30pm — No Comments
This is a project I've been working on for some time to help improve the missed opportunity rate (no-show rate) at all medical centers. It demonstrates how to extract datasets from an SQL server and load them directly into an R environment. It also demonstrates the entire machine learning process, from engineering new features, tuning and training the model, and finally measuring the model's performance. I would like to share my results and methodology as a guide to help…Continue
Added by James Marquez, MBA, PMP on March 21, 2017 at 8:30am — No Comments
Data is almost everywhere. The amount of digital data that currently exists is now growing at a rapid pace. The number is doubling every two years and it is completely transforming our basic mode of existence. According to a paper from IBM, about 2.5 billion gigabytes of data had been generated on a daily basis in the year 2012. Another article from Forbes informs us…Continue
A data scientist is an umbrella term that describes people whose main responsibility is leveraging data to help other people (or machines) making more informed decisions. The spectrum of data scientist roles is so broad that I will keep this discussion for my next post. What I really want to focus is on what are the distinctive characteristics of a great data scientist.
Over the years that I have worked with data and analytics I have found that this has almost nothing to do with…Continue
Added by Karolis Urbonas on March 20, 2017 at 12:00am — No Comments
Many organizations today have realized that digital transformation is essential to their success.
But many of them forget that focus of a digital transformation is not digitization or even technology, it is the Customer!
Digital Transformation is not easy or small endeavor for any business. Several levers will need to be turned in unison just to ensure…
Added by Sandeep Raut on March 18, 2017 at 5:30am — No Comments
In this post, we consider different approaches for time series modeling. The forecasting approaches using linear models, ARIMA alpgorithm, XGBoost machine learning algorithm are described. Results of different model combinations are shown. For probabilistic modeling the approaches using copulas and Bayesian inference are considered.
Time series analysis, especially forecasting, is an important problem of modern…Continue
Added by Sandeep Raut on January 28, 2017 at 12:46pm — No Comments
Accurate multichannel campaign attribution has stumped the online marketing industry for years. But what if the solution is to stop worrying about attribution, and move to an optimization-driven approach?
You know those photo mosaic images, which suddenly became terribly popular a few years back? They cleverly use lots of individual tiny images to make up one large image. If you look closely you can make out the…Continue
Added by Ian Thomas on January 27, 2017 at 9:30am — No Comments
Added by Sandeep Raut on January 21, 2017 at 10:00am — No Comments
As AI enters our homes through smart home devices or tries to conquer our streets through self-driving cars, one need not be a Luddite to contemplate the potentially heavy implications of AI upon our daily lives and livelihood. The key to answering the question and indeed to understand the ultimate limits of AI is to ask if machines can really think. In this article, I list three tests drawn from three different disciplines to address that…Continue
Added by Srividya Kannan Ramachandran on January 20, 2017 at 12:02pm — No Comments
The profusion of big data alongside helpful nudges from Wall Street has inspired many companies to create Chief Data Officer(CDO) and Chief Data Scientist(CDS) roles. The mandate for these roles remains inchoate much in tune with the incipient nature of application of machine learning and predictive analytics within a large corporate structure.
In a previous post, I had introduced a new paradigm – the…Continue
Added by Srividya Kannan Ramachandran on January 4, 2017 at 6:00pm — No Comments
Aircraft fuel is without a doubt the biggest cost for any airline and often receives widespread attention, especially when airlines hedge their bets the wrong way. Cathay Pacific reported a HK$4.49…Continue
Recently, I have been working on the Neural Networks for Machine Learning course offered by Coursera and taught by Geoffrey Hinton. Overall, it is a nice course and provides an introduction to some of the modern topics in deep learning. However, there are instances where the student has to do lots of extra work in order to understand the topics covered in full detail.
One of the assignments in…Continue
Added by Burak Himmetoglu on December 17, 2016 at 10:00am — No Comments
A popular phrase tossed around when we talk about statistical data is “there is correlation between variables”. However, many people wrongly consider this to be the equivalent of “there is causation between variables”. It’s important to explain the distinction: Correlation means that once we know how one variable changes we can make reasonable deductions about how other variables change There are several variants of correlation:
Data analytics is a mature discipline at this point, and even those outside the data science world generally understand what it’s all about. Modern data science, however, is still new enough to spur questions. Vincent Glanville, Executive Data Scientist at Data Science Central, spoke with Roy Wilds, Chief Data Scientist from PHEMI, a Vancouver-based big data startup, about the best way to educate people…Continue
Added by Roy Wilds, PhD, PHEMI Systems on December 6, 2016 at 8:00am — No Comments
This post is 'not' intended to teach people how to use popular predictive modelling APIs for free. Although, to your surprise, this isn't a far fetched possibility. Trained Machine learning models are basically a function that maps feature vectors to the output variable. Upon querying with a test instance, the model predicts an outcome, assigning…Continue
Added by Ashish kumar on November 28, 2016 at 5:00pm — No Comments