10 Myths About Data Scientists
In the nascent field of Data Science, myths are abound. Here’s my top 10, scoured from the internet (where better than to find a myth or two?). Myth #1: It’s ...
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DSC Webinar Series: Optimize the Data Supply Chain
Every organization is aiming to produce more comprehensive understanding of their customers, their business operations and their risks, through data. Most organizations a...
Taming 1.5 Billion Rows of "Big Apple” Data
Diving into the many underlying trends throughout the entire 1.5 Billion rows of NYC Taxi data with Pivot Billion The age of data has arrived. With it, more and more data...
One Shot Learning and Other Strategies for Reducing Training Data
Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications. Here are five st...
Data-driven Marketing Strategy: Spatial Analytics for Micro-marketing
Data-driven Marketing Strategy: Spatial Analytics for Micro-marketing Organizations, often in their me-too hurry to adopt a new technology, just pour their old-wine (data...
DSC Webinar Series: Data Prep & Automated ML: Better Predictions for Consensus
Financed smartphones are a magnet for identity theft, leaving retailers in the digital and telecommunication industry vulnerable to fraud. Consensus, a Target-owned subsi...
Apache Kafka + KSQL + TensorFlow for Data Scientists via Python + Jupyter Notebook
Why would a data scientist use Kafka Jupyter Python KSQL TensorFlow all together in a single notebook? There is an impedance mismatch between model development using Pyth...
Bill Schmarzo's Retrospective: Data Science, ML, Big Data Analytics, and more
Bill Schmarzo, also known as the “Dean of Big Data” is CTO at Hitachi Vantara, and former CTO at Dell EMC. He authored a series of articles on analytic applications...
Advice to a fresh graduate for getting a job in AI/ Data Science
After a recent webinar, I was asked about advice for getting a job in AI for a fresh graduate This is a good question and not often answered Here are my thoughts Backgrou...
Doctors are from Venus, Data Scientists from Mars – or Why AI/ML is Moving so Slowly in Healthcare
Summary: The world of healthcare may look like the most fertile field for AI/ML apps but in practice it’s fraught with barriers. These range from cultural differences...