- How to Lie with Data - Apr 20, 2017.
We expect data scientists to be objective, but intentionally or not, they can produce results that mislead. We examine three common types of “lies” that Data Scientists should be aware of.
- KDnuggets™ News 17:n15, Apr 19: Forrester vs Gartner on Data Science/Analytics Platforms; 5 Machine Learning Projects You Can No Longer Overlook - Apr 19, 2017.
Also Top mistakes data scientists make when dealing with business people; New Online Data Science Tracks for 2017; Cartoon: Why AI needs help with taxes.
- Top mistakes data scientists make when dealing with business people - Apr 13, 2017.
There are no cover articles praising the fails of the many data scientists that don’t live up to the hype. Here we examine 3 typical mistakes and how to avoid them.
- What we can learn from AI mistakes - Dec 19, 2016.
Because of recent innovations and research in AI, we have seen AI performing best in some very important tasks and even worst in even simple tasks. So the question is, Why is it that AI can look so brilliant and so stupid at the same time?
- Avoid These Common Data Visualization Mistakes - Feb 8, 2016.
Data Visualization is a handy tool which can lead to interesting discoveries about the data, which otherwise wouldn’t have been possible. But, there are common mistakes which could produce the misdirecting results. Learn what are they and how you can avoid them.
- 7 Common Data Science Mistakes and How to Avoid Them - Jan 26, 2016.
Data scientist in business is as similar as to that of a detective: discovering the unknown. But, while venturing onto this journey they do tend to fall into the pitfalls. Understand, how these mistakes are made and how you can avoid them.
- Sentiment Analysis & Predictive Analytics for trading. Avoid this systematic mistake - Jan 25, 2016.
The financial market is the ultimate testbed for predictive theories. With this post we want to highlight the common mistakes, observed in the world of predictive analytics, when computer scientists venture into the field of financial trading and quantitative finance.
- KDnuggets™ News 15:n08, Mar 11: 7 common Machine Learning mistakes; Statistical Reasoning - Mar 11, 2015.
7 common mistakes when doing Machine Learning; 10 Predictive Analytics Influencers; Kaiser Fung on Why Statistical Reasoning is more important than Number Crunching; The Elements of Data Analytic Style - checklist; KDD-2017.
- 7 common mistakes when doing Machine Learning - Mar 7, 2015.
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data. For Big Data, it pays off to analyze the data upfront and then design the modeling pipeline accordingly.
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