dhidasif3d

12-Month-Forecast-With-LSTM

This is an example of LSTM used to forecast the next 12 months on the Air Passengers dataset.

abacus_mmm

bayesian_mmm

Code for the article Modeling Marketing Mix using PyMC3

BayesianMMM

(ml) - python implementation of bayesian media mix modelling with shape and carryover effect

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

ISO-3166-Countries-with-Regional-Codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

LLM_HF_course

medium_posts

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

dhidasif3d/12-Month-Forecast-With-LSTM

This is an example of LSTM used to forecast the next 12 months on the Air Passengers dataset.

dhidasif3d/abacus_mmm

dhidasif3d/bayesian_mmm

Code for the article Modeling Marketing Mix using PyMC3

dhidasif3d/BayesianMMM

(ml) - python implementation of bayesian media mix modelling with shape and carryover effect

dhidasif3d/deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

dhidasif3d/ISO-3166-Countries-with-Regional-Codes

ISO 3166-1 country lists merged with their UN Geoscheme regional codes in ready-to-use JSON, XML, CSV data sets

dhidasif3d/lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

dhidasif3d/LLM_HF_course

dhidasif3d/medium_posts

dhidasif3d/prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

dhidasif3d/TransferLearningTimeSeries

Transfer Learning for Time Series Prediction Task