Category: AI / Machine Learning / Deep Learning
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Trends in Data Science for 2020 & 2021
I have not published any article for more than 2 months. It was extremely busy for the re-work on different project schedules and additional administrative work due to the coronavirus crisis. For this time, I would like to share an article planned to published by the end of January 2020. It’s about the coming trend…
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AI Canvas to Work out AI
In this article, I would like to share the simple decision-making tool named AI Canvas and being used in MBA graduates at the university of Toronto’s Rotman School of Management, by professor Ajay Agrawal, University of Toronto. Before going into further details, it is vital to declare that AI / Data Science / Prediction…
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Hardware Investment on Data Science in 2019/20
In this article, I would like to share some technical staff rather than high level data science topic for managers. There are more and more organizations investing in Machine Learning (mostly TensorFlow) including the installation and configuration of new servers and GPU for the intensive computations. Different hardware or cloud service will be discussed. Development…
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Citizen Data Scientist VS Data Scientist
After Gartner defined the term “Citizen Data Scientist” since 2016, there are some large corporations implementing their own data services based on the recommendation by Gartner. Nevertheless, it is vital to understand that Citizen Data Scientist should lead a different role compared to Data Scientist and not possible to replace data scientist as “Power User”…
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Don’t abuse the term “AI” – Artificial Intelligence
There are lots of people introducing themselves as “AI experts” since 2017. However, I am not sure how many of them are understanding the difference between Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). Most of the self-claimed AI experts are doing some ML or DL tasks in a particular area like Object Recognition (image…