"Hey Kostas... I can't thank you enough for posting your analysis on time series. It really helped me a lot to understand what I was struggling with. keep up the good work"
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Nitin Garg commented on Kostas Hatalis's blog post Tutorial: Multistep Forecasting with Seasonal ARIMA in PythonNitin Garg liked Kostas Hatalis's blog post Tutorial: Multistep Forecasting with Seasonal ARIMA in PythonNitin Garg liked Kostas Hatalis's blog post Tutorial: Multistep Forecasting with Seasonal ARIMA in Python
Kostas Hatalis liked William Vorhies's blog post Temporal Convolutional Nets (TCNs) Take Over from RNNs for NLP Predictions
Rohan Kotwani commented on Kostas Hatalis's blog post Swarm Optimization: Goodbye Gradients"Check out kernelml https://github.com/Freedomtowin/kernelml"
Mithun Ghosh liked Kostas Hatalis's blog post Tutorial: Multistep Forecasting with Seasonal ARIMA in PythonKostas Hatalis's blog post was featuredTutorial: 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
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- 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/
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- Years of Experience:
- 5
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- Lehigh University
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- Research Assistant
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Kostas Hatalis's Blog
What is intelligence?
Posted on March 15, 2018 at 12:30pm 0 Comments 1 Like
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…
Continue Basics of Bayesian Decision Theory
Posted on March 15, 2018 at 12:00pm 0 Comments 1 Like
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…
Swarm Optimization: Goodbye Gradients
Posted on March 15, 2018 at 12:00pm 2 Comments 4 Likes
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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