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This repository covers essential techniques for time series analysis and forecasting. It covers data manipulation and visualization using Numpy and Pandas, time series analysis with Statsmodels, ARIMA models, deep learning methods like RNNs, LSTM, GRU, etc. and Facebook's Prophet library.

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02-Pandas-Data-Visualization-Exercise.ipynb
02-Pandas-Data-Visualization-Exercise.ipynb
 
 
02-RNN-Exercise.ipynb
02-RNN-Exercise.ipynb
 
 
04-BONUS-Multivariate-RNN.ipynb
04-BONUS-Multivariate-RNN.ipynb
 
 
04-Statsmodels-Time-Series-Exercises.ipynb
04-Statsmodels-Time-Series-Exercises.ipynb
 
 
05-Pandas-Time-Series-Exercises-SET-ONE.ipynb
05-Pandas-Time-Series-Exercises-SET-ONE.ipynb
 
 
07-Time-Series-with-Pandas-Project-Exercise-SET-TWO.ipynb
07-Time-Series-with-Pandas-Project-Exercise-SET-TWO.ipynb
 
 
10-Forecasting-Exercises.ipynb
10-Forecasting-Exercises.ipynb
 
 
ACF and PACF.ipynb
ACF and PACF.ipynb
 
 
ARMA and ARIMA modeling.ipynb
ARMA and ARIMA modeling.ipynb
 
 
Alcohol Sales Forecasting using LSTMs.ipynb
Alcohol Sales Forecasting using LSTMs.ipynb
 
 
Appliances Energy Prediction using LSTMs(Multivariate Time Series).ipynb
Appliances Energy Prediction using LSTMs(Multivariate Time Series).ipynb
 
 
Autoregression (AR) with Statsmodels.ipynb
Autoregression (AR) with Statsmodels.ipynb
 
 
Choosing ARIMA Orders.ipynb
Choosing ARIMA Orders.ipynb
 
 
Customizing plots with Pandas.ipynb
Customizing plots with Pandas.ipynb
 
 
Dealing with Datetime Index objects.ipynb
Dealing with Datetime Index objects.ipynb
 
 
Descriptive Statistics and Tests.ipynb
Descriptive Statistics and Tests.ipynb
 
 
ETS Decomposition.ipynb
ETS Decomposition.ipynb
 
 
Exponentially Weighted Moving Averages (EWMA).ipynb
Exponentially Weighted Moving Averages (EWMA).ipynb
 
 
Facebook Prophet Evaluation.ipynb
Facebook Prophet Evaluation.ipynb
 
 
Facebook Prophet Seasonality.ipynb
Facebook Prophet Seasonality.ipynb
 
 
Facebook Prophet Trend.ipynb
Facebook Prophet Trend.ipynb
 
 
Facebook's Prophet Time Series Forecasting.ipynb
Facebook's Prophet Time Series Forecasting.ipynb
 
 
Forecasting at Scale.pdf
Forecasting at Scale.pdf
 
 
Introduction to Forecasting Models.ipynb
Introduction to Forecasting Models.ipynb
 
 
Keras Basics.ipynb
Keras Basics.ipynb
 
 
Rolling and Expanding.ipynb
Rolling and Expanding.ipynb
 
 
SARIMAX - Seasonal Autoregressive Integrated Moving Average Modeling.ipynb
SARIMAX - Seasonal Autoregressive Integrated Moving Average Modeling.ipynb
 
 
Seasonal Autoregressive Integrated Moving Average - SARIMAX Modeling.ipynb
Seasonal Autoregressive Integrated Moving Average - SARIMAX Modeling.ipynb
 
 
Statsmodels Introduction.ipynb
Statsmodels Introduction.ipynb
 
 
Time Resampling.ipynb
Time Resampling.ipynb
 
 
Time Series Analysis using Holt-Winters Method.ipynb
Time Series Analysis using Holt-Winters Method.ipynb
 
 
Time Shifting.ipynb
Time Shifting.ipynb
 
 
Vector AutoRegression(VAR) Modeling.ipynb
Vector AutoRegression(VAR) Modeling.ipynb
 
 
Vector AutoRegressive Moving Average (VARMA) Modeling.ipynb
Vector AutoRegressive Moving Average (VARMA) Modeling.ipynb
 
 
Visualizing time series data with Pandas.ipynb
Visualizing time series data with Pandas.ipynb
 
 
Visualizing time series data.ipynb
Visualizing time series data.ipynb
 
 
alcohol_sales_forecaster.keras
alcohol_sales_forecaster.keras
 
 
appliances_energy_predictor.h5
appliances_energy_predictor.h5
 
 
tsa_course_env.yml
tsa_course_env.yml
 
 
vehicle_miles_travelled_forecaster.h5
vehicle_miles_travelled_forecaster.h5
 
 

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This repository covers essential techniques for time series analysis and forecasting. It covers data manipulation and visualization using Numpy and Pandas, time series analysis with Statsmodels, ARIMA models, deep learning methods like RNNs, LSTM, GRU, etc. and Facebook's Prophet library.

Topics

python deep-learning recurrent-neural-networks trends statsmodels forecasting-models time-series-analysis sarimax facebook-prophet-forecasting seasonality time-series-forecasting arima-forecasting varmax sarima-model holt-winters-forecasting autocorrelation-function augmented-dickey-fuller-test stationarity-test partial-autocorrelation-function
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