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Khosrow Hassibi, PhD
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Machine Learning vs. Traditional Statistics: Different upbringings, different philosophies
"Machine Learning (ML)" and "Traditional Statistics(TS)" have different philosophies in their approaches. With "Data Science" in the forefront getting lots of attention and interest, I like to dedicate this blog to discuss the differentiation between the tw...
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10 Required Non-technical Skills for a Data Scientist
"Data Science(DS)" is nothing new but the term itself and the recent level of interest in it. As a practice it has commercially (not academically) existed for more than 25 years, mainly under "Data Mining (DM)" and "predictive analytics(PA)," since early 19...
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10 Required Non-technical Skills for a Data Scientist
"Data Science(DS)" is nothing new but the term itself and the recent level of interest in it. As a practice it has commercially (not academically) existed for more than 25 years, mainly under "Data Mining (DM)" and "predictive analytics(PA)," since early 19...
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10 Required Non-technical Skills for a Data Scientist
"Data Science(DS)" is nothing new but the term itself and the recent level of interest in it. As a practice it has commercially (not academically) existed for more than 25 years, mainly under "Data Mining (DM)" and "predictive analytics(PA)," since early 19...
Add a comment...

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10 Required Non-technical Skills for a Data Scientist
"Data Science(DS)" is nothing new but the term itself and the recent level of interest in it. As a practice it has commercially (not academically) existed for more than 25 years, mainly under "Data Mining (DM)" and "predictive analytics(PA)," since early 19...
Add a comment...

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10 non-technical skills required for of a data scientist
"Data Science(DS)" is nothing new but the term itself and the recent level of interest in it. As a practice it has commercially (not academically) existed for more than 25 years, mainly under "Data Mining (DM)" and "predictive analytics(PA)," since early 19...
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What is BuDAI?
Data science[1] (covering data mining and related practices) is a multidisciplinary field that requires knowledge of a number of different
skills, practices, and technologies, including but not limited to machine learning,
pattern recognition, mathematics, ...
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The Age of Data Innocence is Over
When I try to explain Data Science and Analytics to business people or those interested in these fields, I use the following example to describe the four pillars of: Data, Platform/Tools, Algorithms, and know-how. To me, "data" is like a collection of bones...
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Analytics Divide and Big Data
For more information and orders, visit the book site for " High-Performance Data Mining and Big Data Analytics: The Story of Insight from Big Data " ( http://bigdataminingbook.info   ). In a research report
on analytics by MIT and IBM (Kiron, et al. 2011) ,...
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