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Kostas Hatalis
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  • Bethlehem, PA
  • United States
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Man liked Kostas Hatalis's blog post Tutorial: Multistep Forecasting with Seasonal ARIMA in Python
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Tutorial: Multistep Forecasting with Seasonal ARIMA in Python

When trend and seasonality is present in a time series, instead of decomposing it manually to fit an ARMA model using the Box Jenkins method, another very popular method is to use the seasonal autoregressive integrated moving average (SARIMA) model which is a generalization of an ARMA model. SARIMA models are denoted SARIMA(p,d,q)(P,D,Q)[S], where S refers to the number of periods in each season, d is the degree of differencing (the number of times the data have had past values subtracted), and…See More
Apr 13
Gary Baggett liked Kostas Hatalis's blog post Swarm Optimization: Goodbye Gradients
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tarek Jan liked Kostas Hatalis's blog post Probabilistic Forecasting: Learning Uncertainty
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George Joseph liked Kostas Hatalis's blog post What is intelligence?
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Kim Evarista liked Kostas Hatalis's blog post Basics of Bayesian Decision Theory
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ANISH XAVIER liked Kostas Hatalis's blog post Swarm Optimization: Goodbye Gradients
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Arunprasath Shankar commented on Kostas Hatalis's blog post Swarm Optimization: Goodbye Gradients
"can you share the code you used to create the convergence diagram above.  [email protected]"
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Kostas Hatalis posted blog posts
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Profile Information

Short Bio
I am a Ph.D. candidate in electrical engineering at Lehigh University. My research focuses on converging machine learning, signal processing, and swarm optimization for time series analysis, probabilistic forecasting, and pattern recognition.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/hatalis/
Field of Expertise
Machine Learning
Professional Status
Student
Years of Experience:
5
Your Company:
Lehigh University
Industry:
Academia
Your Job Title:
Research Assistant
How did you find out about DataScienceCentral?
LinkedIn
Interests:
Contributing, Networking, New venture

Kostas Hatalis's Blog

Tutorial: Multistep Forecasting with Seasonal ARIMA in Python

Posted on April 12, 2018 at 10:30am 0 Comments

When trend and seasonality is present in a time series, instead of decomposing it manually to fit an ARMA model using the Box Jenkins method, another very popular method is to use the seasonal autoregressive integrated moving average (SARIMA) model which is a generalization of an ARMA model. SARIMA models are denoted SARIMA(p,d,q)(P,D,Q)[S], where S refers to the number of periods in each season, d is the degree of differencing (the number of times the…

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What is intelligence?

Posted on March 15, 2018 at 12:30pm 0 Comments

This is an AI related post on the nature and philosophy of intelligence. In the various fields that study the mind, human or otherwise, there are many definitions (and lack of) for the term 'intelligence'. What is it, how can we measure it, how can we reproduce it? What implications does this have in the fields of AI, machine learning, and data science? A paper [1] by Shane Legg and Marcus Hutter, attempted to survey the definition from these various fields. The following are some sample…

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Basics of Bayesian Decision Theory

Posted on March 15, 2018 at 12:00pm 0 Comments

The use of formal statistical methods to analyse quantitative data in data science has increased considerably over the last few years. One such approach, Bayesian Decision Theory (BDT), also known as Bayesian Hypothesis Testing and Bayesian inference, is a fundamental statistical approach that quantifies…

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Swarm Optimization: Goodbye Gradients

Posted on March 15, 2018 at 12:00pm 1 Comment

Fish schools, bird flocks, and bee swarms. These combinations of real-time biological systems can blend knowledge, exploration, and exploitation to unify intelligence and solve problems more efficiently. There’s no centralized control. These simple agents interact locally, within their environment, and new…

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