Time Series Analysis & Forecasting of Restaurant visitor. EDA, Forecasting with Prophet, arima and h2o auto ml for regression.
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Updated
Aug 25, 2018 - R
Time Series Analysis & Forecasting of Restaurant visitor. EDA, Forecasting with Prophet, arima and h2o auto ml for regression.
Files for compiling my presentation about H2O.ai.
Este proyecto "databases-trikis" es una aplicación que utiliza SQLAlchemy, Redis y H2O.
Build your own Recommendation Systems !!!
This notebook is designed to interactively guide the user through an end-to-end process for deploying an automated machine learning workflow utilizing h2o.ai's autoML function. The user is simply required to select a dataset and choose a variable they would like to predict before running the automation. The user can choose to run the automation …
This repository has all data science machine learning projects.
Bank Customer Churn Prediction using ANN and H2O Auto ML models
R package consisting of functions and tools to facilitate the use of traditional time series and machine learning models to generate forecasts on univariate or multvariate data. Different backtesting scenarios are available to identify the best performing models.
Identify the characteristics of customers who more likely to respond and commit to a term deposit and use Automatic Machine Learning H2O AutoML to make prediction on whether or not a certain customer would buy a term deposit.
We will leverage population's information on immunization, mortality, social- economic and other health related factors and use Automatic Machine Learning H2O AutoML to make prediction on life expectancy of a certain population. We will also use Variable Importance Plot, Partial Dependence Plot, and SHAP Summary Plot to explain how each of our f…
An investigation on the use of shapley explanations for unsupervised anomaly-detection models
This is an end-to-end network intrusion detection model with H2O AutoML, Mlflow, Streamlit, and FastAPI which can classify network activities as normal or anomalous
A directory of common utilities and use cases, implemented in Python
Interpreting coefficients and results of the following models: 1. Logistic Regression 2. Random Forest 3. AutoML (H2O)
Machine Learning projects using H2O library.
Final project of the Data Analytics bootcamp. Ironhack Barcelona. December 2022
Energy usage prediction with H2O AutoML
Various Jupyter Notebooks for a Kaggle Competition
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