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Jason Li
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  • Toronto
  • Canada
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Profile Information

Short Bio
I am a passionate engineer. I make great content with data, do awesome data science, produce creative data art, and write motivated technical articles.
My Web Site Or LinkedIn Profile
http://ecmapping.com
Field of Expertise
Analytics, Data Integration, Visualization, Other, Data Science
Professional Status
Technical
Years of Experience:
20
Your Company:
Canada
Industry:
Transportation
Your Job Title:
Senior Policy Advisor
How did you find out about DataScienceCentral?
DataScienceCentral referred my article
Interests:
Networking
What is your Favorite Data Mining or Analytical Website?
http://ecmapping.com
What Other Analytical Website do you Recommend?
http://https://www.media.mit.edu/

Jason Li's Blog

Differences between Data Mining and Predictive Analytics

Posted on October 12, 2016 at 5:30pm 7 Comments

What is Data Mining?

Data mining is an integrated application in the Data Warehouse and describes a systematic process for pattern recognition in large data sets to identify conclusions and relationships. Using statistical methods, or genetic algorithms, data files can be automatically searched for statistical anomalies, patterns or rules.

Wikipedia defines Data Mining as “Data mining is an interdisciplinary subfield of computer science. It is the computational process…

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6 Ways Internet of Things is Already Changing Everything around Us

Posted on August 11, 2016 at 6:30am 0 Comments

Connected devices, Smart City, home automation, e-health, Big Data ... In recent years, the concepts of communicating objects have multiplied. In reality, they are all one facet of the same upheaval - the Internet of Things.

Cars can be driven without a driver, TVs are going online, and heating systems are activated automatically to the arrival of the residents. The Internet is making many processes in daily life easier. The Internet of Things, or IoT, which enable devices to…

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12 Useful Resources to Explore the World of Big Data‎

Posted on July 21, 2016 at 5:20am 0 Comments

Big data, this flood of data that scares some people, has moved from hype to reality. However, collecting more data does not always mean better insights. The exponential data growth via social networks and soon by connected objects tomorrow has become big challenges. The cursor should now be on the exploitation of useful data; or somebody call it Smart Data. How to achieve this mission to make intelligent data? Please see the Big Data posts from…

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