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arima

Arima Notes

assortopt

Assortment optimization under consider-then-choose choice models

awesome-awesomeness

A curated list of awesome awesomeness

code_snippets

customizing-shiny-apps

data-science-and-machine-learning-projects-dojo

collections of data science, machine learning and data visualization projects with pandas, sklearn, matplotlib, tensorflow2, Keras, various ML algorithms like random forest classifier, boosting, etc

data-science-books

datalab-examples

The repository contains examples of ipython notebooks that can be used with Datalab to connect to GCP components.

deep-learning-with-r-notebooks

R notebooks for the code samples of the book "Deep Learning with R"

deeplearningfortimeseriesforecasting

A tutorial demonstrating how to implement deep learning models for time series forecasting

dynamicmnl

Greedy-Like Algorithms for Dynamic Assortment Optimization Under Multinomial Logit Preferences

dynamicnp

Approximation Algorithms for Dynamic Assortment Optimization Models

econometricswithr

📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)

euclidean-distance

Computes the Euclidean distance between two arrays.

forecasting

Time Series Forecasting Best Practices & Examples

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hybrid-forecasting-method-

Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors

learning-to-learn

lists

The definitive list of lists (of lists) curated on GitHub

m4

M4

m4-methods

Includes the source code of the methods which participated in the M4 Competition

m4comp2018

The R package M4comp2018 contains the 100000 time series from the M4-competition (https://www.m4.unic.ac.cy/)

m5-accuracy-competition

My second place solution in the M5 Accuracy competition

m5-methods

Data, Benchmarks, and methods submitted to the M5 forecasting competition

m6

M6-Forecasting competition

ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

r-source

Read-only mirror of R source code from https://svn.r-project.org/R/, updated hourly. See the build instructions on the wiki page.

shapforxgboost

SHAP (SHapley Additive exPlnation) visualization for 'XGBoost' in 'R'