Download DS-GA 3001.001 Special Topics in Data Science: Probabilistic Time Series Analysis PDF Free - Full Version
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About DS-GA 3001.001 Special Topics in Data Science: Probabilistic Time Series Analysis
This graduate level course covers probabilistic time series analysis methods like ARIMA, Kalman filtering, hidden Markov models, Gaussian processes, and recurrent neural networks. The course emphasizes generative models for time series and their inference and learning. It includes problem sets, a midterm exam, final project, and lab assignments. The final project involves applying algorithms to real data or improving existing methods in groups of 2-3 students. Lectures are on Mondays and labs are on Wednesdays. The course uses Python and provides video recordings of lectures.
Detailed Information
| Author: | ['Ougni Chakraborty'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 3 |
| Language: | English |
| Format: | |
| Price: | FREE |
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