Ephemeral Content: How & Why to Invest in Content That Disappears

Last year, Sony Pictures earned over 45 million impressions and made over a million in incremental movie ticket purchases.
While these metrics are impressive, the method by which these metrics were earned might be even more impressive — content that disappeared on Snapchat.
Snapchat Stories is a prime feature of the app.

Read Full Story

Rakuten Marketing Data Breaks down Consumer Habits During the First Holiday Shopping Events of the Season

Larger Purchases Made on Single’s Day and a Higher Frequency of Orders During Click Frenzy
Rakuten Marketing have released findings from data collected on Single’s Day and Click Frenzy which for the first time ever, fell over three consecutive days (Nov 11 – 13).

Read Full Story

Crawling the internet: data science within a large engineering system

by BILL RICHOUXCritical decisions are being made continuously within large software systems. Often such decisions are the responsibility of a separate machine learning (ML) system. But there are instances when having a separate ML system is not ideal. In this blog post we describe one of these instances — Google search deciding when to check if web pages have changed.

Read Full Story

How to Become an Influencer in Your Industry

Influencer marketing has skyrocketed since it first made its mark.
That’s very much due to the way purchasing decisions have changed over the years. In 2018, a study found that only 4% of people trusted celebrity endorsements. This is probably because they prefer to seek product and service recommendations from those who are, above all, knowledgeable and credible.

Read Full Story

Machine learning APIs: which performs best?

Amazon ML (Machine Learning) made a lot of noise when it came out last month. Shortly afterwards, someone posted a link to Google Prediction API on HackerNews and it quickly became one of the most popular’s posts. Google’s product is quite similar to Amazon’s but it’s actually much older since it was introduced in 2011.

Read Full Story

CRaP at Amazon and Advice for Amazon Sellers

Amazon recently made the news by publicly announcing that it is targeting hard to sell items, so called Can’t Realize a Profit (CRaP) for removal from its all-powerful sales channel.  Such items are believed to be those that have a low revenue for the cost to ship. Essentially, the shipping costs outdoes the contribution margin of the item. That sounds easy and makes sense.

Read Full Story

Once Again: Prefer Confidence Intervals to Point Estimates

Today I saw a claim being made on Twitter that 17% of Jill Stein supporters in Louisiana are also David Duke supporters. For anyone familiar with US politics, this claim is a priori implausible, although certainly not impossible.
Given how non-credible this claim struck me as being, I decided to look into the origin of this number of 17%.

Read Full Story

Headcount goals, feature factories, and when to hire those mythical 10x people

When I started building up a tech team for Better, I made a very conscious decision to pay at the high end to get people. I thought this made more sense: they cost a bit more money to hire, but output usually more than compensates for it. Many fellow CTOs, some went for the other side of the spectrum. This was a mystery to me, until it all made sense to me.

Read Full Story

How to make a Career Transition from Mainframe Engineer to Data Scientist?

Alap’s Career Transition Success Story
Learning at par Industry-standards with Industry experts made my Career Transition possible
Background
Education: BE in Electrical
Previous ProfileCompany: CGIProfile: Software Engineer (Mainframe) Project: John Hancock (Manulife) Insurance Services Domain: InsuranceLocation: India
Current ProfileCompany: CGIProfile: Lead Business AnalystProject: ER

Read Full Story

Exploring LSTMs

LSTMs are behind a lot of the amazing achievements deep learning has made in the past few years, and they’re a fairly simple extension to neural networks under the right view. So I’ll try to present them as intuitively as possible – in such a way that you could have discovered them yourself.
But first, a picture:
Aren’t LSTMs beautiful? Let’s go.

Read Full Story

JMP Publishes Exercises to Accompany Data Mining Techniques (3rd Edition)

I am pleased to announce that the JMP division of SAS has made available a set of exercises I developed for use with Data Mining Techniques. I am grateful to my employer, Tripadvisor, for supplying the data used for these exercises. The exercises and data sets are free and available for download at https://www.jmp.com/en_us/academic/data-mining-techniques.html.

Read Full Story

Does financial support in Australia favour residents born elsewhere? Responding to racism with data

Seeing a racist outburst made me wonder whether the Australian Government unfairly supports people based on their background. Using data from the Australian Government and Bureau of Statistics, I couldn’t find compelling evidence of this being true. Don’t believe me? Read on and see what you make of the data.

Read Full Story

Monocular Visual Odometry using OpenCV

Last month, I made a post on Stereo Visual Odometry and its implementation in MATLAB.
This post would be focussing on Monocular Visual Odometry, and how we can implement it in OpenCV/C++.
The implementation that I describe in this post is once again freely available on github.
It is also simpler to understand, and runs at 5fps, which is much faster than my older stereo implementation.

Read Full Story

Data Science News from Microsoft Ignite 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Here they are in my order of importance (based upon my opinion).
Azure Synapse
I think this announcement will have a very large and immediate impact. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake.

Read Full Story