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Mab Alam
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Latest Activity

Daniel Reimann liked Mab Alam's blog post Outlier detection with time-series data mining
Thursday
hameed ali liked Mab Alam's blog post Outlier detection with time-series data mining
Thursday
hameed ali liked Mab Alam's blog post Time-series data mining & applications
Thursday
shishir goel liked Mab Alam's blog post Time-series data mining & applications
Jun 13
TAYLAN ZAFER BALİ liked Mab Alam's blog post Outlier detection with time-series data mining
Jun 11
Mab Alam's blog post was featured

Outlier detection with time-series data mining

In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:Trend analysisOutlier/anomaly detectionExamining shocks/unexpected variationAssociation analysisForecastingPredictive analyticsHere I am focusing on outlier and anomaly detection. Important to note that outliers and anomalies can be synonymous, but…See More
Jun 10
Gerardo Rojas liked Mab Alam's blog post Outlier detection with time-series data mining
Jun 7
Mab Alam posted a blog post

Outlier detection with time-series data mining

In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:Trend analysisOutlier/anomaly detectionExamining shocks/unexpected variationAssociation analysisForecastingPredictive analyticsHere I am focusing on outlier and anomaly detection. Important to note that outliers and anomalies can be synonymous, but…See More
Jun 6
Edward Ghafari liked Mab Alam's blog post Data Science meets System Dynamics
May 31
Mab Alam posted a blog post

Time-series data mining & applications

A time series is a sequence of data points recorded at specific time points - most often in regular time intervals (seconds, hours, days, months etc.). Every organization generates a high volume of data every single day – be it sales figure, revenue, traffic, or operating cost. Time series data mining can generate valuable information for long-term business decisions, yet they are underutilized in most organizations. Below is a list of few possible ways to take advantage of time series…See More
May 31
Mab Alam's blog post was featured

Time-series data mining & applications

A time series is a sequence of data points recorded at specific time points - most often in regular time intervals (seconds, hours, days, months etc.). Every organization generates a high volume of data every single day – be it sales figure, revenue, traffic, or operating cost. Time series data mining can generate valuable information for long-term business decisions, yet they are underutilized in most organizations. Below is a list of few possible ways to take advantage of time series…See More
May 31
Mab Alam replied to William Vorhies's discussion Will all that data in the hands of Google or Facebook lead to a good result or bad?
"Uncomfortable and provocative indeed. People's behavior is already being manipulated by external agents (e.g. what movie to watch, where to go for the next vacation). The way our mental decision system works, it's only a matter of time…"
May 28
Mab Alam updated their profile
May 27
Andrea Taverna liked Mab Alam's blog post Data Science meets System Dynamics
May 27
Mab Alam posted a blog post

Data Science meets System Dynamics

Developed at MIT’s Sloan School of Management in 1950s system dynamics is a methodological approach to model the behavior of complex systems, where change in one component leads to change in others (like the dominos effect with feedback loops added). This approach is widely applied in industries such as healthcare, disease research, public transportation, business management and revenue forecasting. The most famous application of system dynamics probably is in…See More
May 26
Mab Alam's blog post was featured

Data Science meets System Dynamics

Developed at MIT’s Sloan School of Management in 1950s system dynamics is a methodological approach to model the behavior of complex systems, where change in one component leads to change in others (like the dominos effect with feedback loops added). This approach is widely applied in industries such as healthcare, disease research, public transportation, business management and revenue forecasting. The most famous application of system dynamics probably is in…See More
May 26

Profile Information

Short Bio
I am a PhD economist working with data for 12 years (grad schools included). Published widely in academic journals and served as a reviewer. Interested in a broad range of issues in data science and machine learning - including time series, forecasting and system dynamics. I like people who think outside box, who make a difference in the process of re-inventing wheels.
My Web Site Or LinkedIn Profile
http://twitter.com/DataEnthus
Field of Expertise
Data Science, Machine Learning, Business Analytics, BI
Professional Status
Technical
Years of Experience:
12
Your Job Title:
Research Economist
Interests:
Contributing, Networking

Mab Alam's Blog

Outlier detection with time-series data mining

Posted on June 1, 2018 at 2:00pm 0 Comments

In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:

  1. Trend analysis
  2. Outlier/anomaly detection
  3. Examining shocks/unexpected variation
  4. Association analysis
  5. Forecasting
  6. Predictive analytics

Here I am focusing on outlier…

Continue

Time-series data mining & applications

Posted on May 27, 2018 at 9:00pm 0 Comments

A time series is a sequence of data points recorded at specific time points - most often in regular time intervals (seconds, hours, days, months etc.). Every organization generates a high volume of data every single day – be it sales figure, revenue, traffic, or operating cost. Time series data mining can generate valuable information for long-term business decisions, yet they are underutilized in most organizations. Below is a list of few possible ways to…

Continue

Data Science meets System Dynamics

Posted on April 23, 2018 at 5:30pm 0 Comments

Developed at MIT’s Sloan School of Management in 1950s system dynamics is a methodological approach to model the behavior of complex systems, where change in one component leads to change in others (like the dominos effect with feedback loops added). This approach is widely applied in industries such as healthcare, disease research, public transportation, business management and revenue forecasting. The most famous application of system dynamics probably is in…

Continue

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