Archive for the ‘Machine Learning’ Category

Are we headed towards Prediction Driven Development?

In Automation, Machine Learning, Prediction on December 2, 2016 at 12:49 pm

In a recent tweet about Sanity Testing,  I started thinking about certain Machine Learning tools in the market which seem to predict defects for various change requests submitted.

Now assuming that this defect prediction tool “actually works”,  it would become extremely useful to conduct an extended Sanity (in the least).  This would lead to major issues caused by the change requests to be resolved even before it gets to the hands of a tester, thereby saving money and time.  Changes keep happening up-to the last minute of a Product release, and this could well be another way to develop Software.


Quick Tip: Anomaly Detection to build trust with Customers

In Automation, Bills, Invoices, Machine Learning on November 21, 2016 at 4:05 pm

In a recent incident, one of my friends took his old vehicle for servicing.  Among other things, a small bulb was replaced and the bill for just that part was a whopping Rs 300/-.  The explanation given to him was that the bulb costs Rs.150/- and the labor was Rs. 150/-. Whereas the same would cost nearly half the price a few months ago. Courtesy a history of maintaining invoices, he was able to question the prices.

He was also at the receiving end for some of his other bills, when he saw some extra charges which were never charged in his earlier bills (which he had maintained).  It was later found out, that these were some “errors”.   I wonder how many people would really do all this.

For people who do not store so many bills/invoices and keep track of unusual deviations in them.  They could be ripped off.

Solution: In these days of digital records (including bills and invoices), a machine learning algorithm called Anomaly Detection could help.  A company could basically spot the outliers or anomalies and strive to eliminate them thereby building trust with their customers.  For the customers, they could benefit if certain flags are reported in their bills whenever a large variation in prices is seen in their invoices for many billing products.

Some bills, payslips etc, could contain breakups of various categories, and any missing category or additional categories can also be flagged.

All in all, a win win for both Customers and Businesses


Quick Tip: Machine Learning can help improve your Customer Service

In Automation, Customer Service, Machine Learning on November 1, 2016 at 5:51 am

In an email to the customer support team of  a well known electronics company, I had asked a simple question before placing an order.  The question was, if one of their products was compatible with a specific OS.  The response from their customer support took about 4 days.  In response to it, I asked them if there were any drivers available.  The response,  “We will let you know when it’s available” took 4 more days. I had already placed an order after looking at some online posts regarding it’s compatibility.  I believe such simple queries can be addressed in their “Automated Response System”.  A typical response could be a set of recommended links (using Machine Learning) which could suggest what customers are saying, or pointing to certain solutions that have been suggested on the net.  Of course they can absolve themselves of any guarantees, if they really do not have a clue (which I doubt).  Oh! and did I mention the product worked fine without any drivers?  Please feel free to leave a comment.

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