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Use .csv dump and get sense of data.
Questions:
- Are the time series stationary?
- What kind of seasonal effects do we see (daily? Monthly? weekly? yearly?)
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Based on our analysis by industry, let's further analyze the trend of returns. Autocorrelation is typically used in signal processing to identify repeating patterns or in finance to identify trends in…
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Idea: Develop translations to advance system understanding on the global information, transmission, and environmental cycles linked to spatially distributed human behavior and organized mitigation, an…
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# Phase 1: MVP Package
Develop a minimal package with the most important functions.
Use this guide: https://py-pkgs.org/03-how-to-package-a-python
## Priority 1 - Core Data and Data Frame Op…
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2021-05-20
Onboarding Task:
* Completed talent Trac assignments
* Register ADP account
Git/GitHub Configuration:
* Installing Git with the admin help of IT
* Adding GitHub certificate to the…
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just to park a link, question with references
https://stats.stackexchange.com/questions/287548/what-is-the-intuition-for-testing-seasonal-difference-with-ocsb-test-and-its-cor
we might need this…
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**Candle information** (might help the model learning candlestick patterns):
- hl2 Price
- hlc3 Price
- ohlc4 Price
```
def upper_shadow(df):
return df['High'] - np.maximum(df['Close'], df…
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To enhance the predictive performance of our models (Linear Regression, Random Forest, Gradient Boosting, LSTM, ARIMA, SARIMA), we need to explore and implement various feature engineering strategies.…
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I've been working on a) replicating the analysis from Huneke et al., 2022 to identify ASC regimes using an unsupervised clustering algorithm (Gaussian Mixture Modelling) and b) seeing if we can track …
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### **What are you proposing?**
* The current log analytics solution is great at showing how things are performing in the moment. When looking at log metrics, users also want to understand where th…