Sriram Sambasivam's repositories
Arima
Arima Notes
awesome-awesomeness
A curated list of awesome awesomeness
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
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
EconometricsWithR
đź“–An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
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.
lists
The definitive list of lists (of lists) curated on GitHub
M4-methods
Includes the source code of the methods which participated in the M4 Competition
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.
python-machine-learning-book-2nd-edition
The "Python Machine Learning (2nd edition)" book code repository and info resource
SHAPforxgboost
SHAP (SHapley Additive exPlnation) visualization for 'XGBoost' in 'R'
statrethinking_winter2019
Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
structural-time-series
Structural Time Series on US electricity demand data
tensorflow
Computation using data flow graphs for scalable machine learning
Time-Series-Clustering
Clustering notes and codes
Time-Series-Forecasting
forecasting notes and codes
tsfeatures
Time series features
WeeklyForecasting
This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model uses the forecasts of 4 sub-models: TBATS, Theta, Dynamic Harmonic Regression ARIMA and a global Recurrent Neural Network (RNN), and optimally combine them using lasso regression.
youtube-for-alexa
youtube for alexa