Auto ML Forecast

	Tech Name	Technique Description	Module (Language)
1	AutoGluon	Automated Machine Learning	Python

Machine Learning Models

	Tech Name	Technique Description	Module (Language)
1	XGBOOST	eXtreme Gradient Boosting	Python
2	LIGHTGBM	Light Gradient-Boosting Machine	Python
3	RANDOM_FOREST	Random Forest (RF)	Python
4	PROPHET	Facebook Prophet	Python

	Tech Name	Technique Description	Module (Language)
1	MULTILAYER_PERCEPTRON	Multilayer Perceptron (MLP)	Python
2	RNN	Recurrent Neural Network	Python (TensorFlow / PyTorch)
3	BlockRNN	Deep RNN for Time Series Forecast	Python (Darts / PyTorch)

	Tech Name	Technique Description	Module (Language)
1	ARIMA_FORECAST	ARIMA Model	R
2	AUTOARIMA_FORECAST	Auto Arima	R
3	AUTOHWS_FORECAST	Auto Holt-Winters Seasonal (HWS)	R
4	AUTOREG_FORECAST	Autoregressive (AR) Forecasting	R
5	BATS_FORECAST	BATS (Box-Cox transformation, ARMA errors, Trend, and Seasonal components)	R
6	CROSTON_FORECAST	Croston’s Method	R
7	DYNAMIC_REGRESSION	Dynamic Regression Model	R
8	HWS_FORECAST	Holt-Winters Seasonal (HWS) Method	R
9	SNAIVE_FORECAST	The Seasonal Naïve forecast	R
10	STL_FORECAST	STL (Seasonal-Trend Decomposition using LOESS) Forecasting	R
11	TBATS_FORECAST	TBATS	R
12	TSLM_REGRESSION	TSLM (Time Series Linear Model) Regression	R
13	VECTOR_REGRESSION	Vector Autoregression (VAR)	R
14	SARIMA	Seasonal AutoRegressive Integrated Moving Average	Python
15	DESLT	Double Exponential Smoothing with Linear Trend	R
16	DESAS	Double Exponential Smoothing with Additive Seasonality	R
17	SES	Simple Exponential Smoothing	Python
18	DES	Double Exponential Smoothing	Python/R
19	ES	Exponential Smoothing	Python
20	TESLTAS	Triple Exponential Smoothing with Linear Trend and Additive Seasonality	Python
21	HarveyPeters	Harvey-Peters Model	Python
22	BSTS	Bayesian Structural Time Series	R
23	TESLTMS	Triple Exponential Smoothing with Linear Trend and Multiplicative Seasonality	R
24	DESMS	Double Exponential Smoothing with Multiplicative Seasonality	Python/R
25	TES	Triple Exponential Smoothing	Python/R