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ta

bukosabino / ta

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Definition mapping from feature name to the actual technical indicator name?

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markdregan
markdregan commented Jan 7, 2022

Wondering if this already exists? If not happy to create if valuable.

I'm looking for a mapping from the column names outputted, to the actual technical indicator it represents.

examples:
momentum_ao == "Momentum, Awesome Oscilator"
momentum_kama == "Momentum, Kaufman’s Adaptive Moving Average (KAMA)"

Can help quickly grasp what the features represent without having to refer back to do

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good first issue
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neural_prophet

ourownstory / neural_prophet

Star 2.2k
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ml-tool-wear

tvhahn / ml-tool-wear

Star 22

Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Monitoring with a Disentangled-Variational-Autoencoder"
deep-learning recall trend beta-vae advanced-manufacturing precision milling anomaly-detection machinery-condition-monitoring masc-thesis latent-spaces tool-wear-monitoring tool-condition-monitoring
  • Updated Jun 1, 2021
  • Jupyter Notebook

ramtiin / Predicting-Stock-Prices-Using-FB-Prophet

Star 8

Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. In this notebook I'm going to try forecasting Google stock price using facebook's prophet model.
machine-learning time-series series forecasting trend prophet
  • Updated Jun 5, 2021
  • Jupyter Notebook

CoryLR / COVID-19-Trend-Map

Star 3

COVID-19-Watch is a public online tool to monitor COVID-19's progression in the United States. The data is updated daily so that anyone can share and bookmark COVID-19 Status Reports of interest (local, state, or national) with their community. Read more on the About page: https://www.covid-19-watch.com/about
map status angular dashboard maps cartography leaflet watch gis usa stats trends trend johns-hopkins-university progression coronavirus covid-19
  • Updated Mar 2, 2022
  • TypeScript
UNICEF_CATS

EmSchoof / UNICEF_CATS

Star 3

Premise of Task: Contextual Alert and Trend System (CATS) is a proof of concept (POC) for an automated system for near real-time media monitoring via GDELT to identify trends and anomalies in the volume of online reports about pre-defined indicator events, at country level. This repository reflects the methodologies used to complete this task.
events alert gdelt trend gdelt-events unicef spike-analysis iqr trend-analysis fips140-2 preparedness
  • Updated Jun 21, 2021
  • Jupyter Notebook

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