Pairs trading using the Kalman Filter and a LSTM forecast model

Contains resources and material for BASH/SHELL programming for data science

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).

A data set based on all arXiv publications, pre-processed for NLP, including structured full-text and citation network

Sample PySpark code for interacting with the Microsoft Academic Graph

A collection of research papers and software related to explainability in graph machine learning.

The WIPO Manual on Open Source Patent Analytics

A web scraping tool to systematically extract the text of scientific papers and corresponding metadata from university accessible journals.

This demo covers Twitter API queries using the tweepy library, basic text processing, visualization, rough sentiment analysis, and visualizing geotags

Repo for Yale Applied Empirical Methods PHD Course

Course material for Bayesian and Modern Statistics, STA601, Duke University, Spring 2015.

😎 Give your xaringan slides some style

Presentation Ninja 幻灯忍者 · 写轮眼

A toolkit for developing and comparing reinforcement learning algorithms.

24 Lessons, 12 Weeks, Get Started as a Web Developer

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow

A use-case focused tutorial for time series forecasting with python

A Python package for time series classification

Top2Vec learns jointly embedded topic, document and word vectors.

proof of concept for a transformer-based time series prediction model

PyTorch Dual-Attention LSTM-Autoencoder For Multivariate Time Series

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models

Python Data Science Handbook: full text in Jupyter Notebooks