GitHub / arunsinghbabal / Time-Series-Predictive-Analytics-for-Hair-Device
Stable temperature is ideal for hair styling, this framework successfully predicts the future power output (correlated with the temperature) based on the historical data to reduce the time lag.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arunsinghbabal%2FTime-Series-Predictive-Analytics-for-Hair-Device
PURL: pkg:github/arunsinghbabal/Time-Series-Predictive-Analytics-for-Hair-Device
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 1.63 MB
Dependencies parsed at: Pending
Created at: over 3 years ago
Updated at: almost 2 years ago
Pushed at: over 2 years ago
Last synced at: almost 2 years ago
Topics: arima-model, data-cleaning, data-visualization, deep, deep-reinforcement-learning, eda, hair-styling, lstm-neural-networks, machine-learning-algorithms, python, sarima-model, time-series-analysis, time-series-forecasting