6440 Open source projects that are alternatives of or similar to Pastas

python implementations of Analyzing Neural Time Series Textbook

A Multipurpose Library for Synthetic Time Series Generation in Python

fastai V2 implementation of Timeseries classification papers.

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

Stock Price Prediction using Machine Learning Techniques

Performance Co-Pilot

Building classifiers using cancer transcriptomes across 33 different cancer-types

This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.

Anything can happen in the next half hour (including spectral timing made easy)!

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

A python library for time-series smoothing and outlier detection in a vectorized way.

Solution to Kaggle - Web Traffic Time Series Forecasting

Python implementation of KNN and DTW classification algorithm

1st place solution

Stock Analysis Tutorial in Python

A replica of the AlphaZero methodology for deep reinforcement learning in Python

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

Run your code in the cloud, with technology so advanced, it feels like magic!

Following repo is the solution to Stock Market Prediction using Neural Networks and Sentiment Analysis

[DEPRECATED] 🔊️ Audio with fastaiv1

visualization of CNN in PyTorch

Implementations of some popular Saliency Maps in Keras

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing

🐳📊🤓Cookiecutter template to launch an awesome dockerized Data Science toolstack (incl. Jupyster, Superset, Postgres, Minio, AirFlow & API Star)

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Images and notebook for camera calibration

Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+

In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.

Jupyter notebook server extension to proxy web services.

Materials for the "Advanced Scikit-learn" class in the afternoon

Label line using matplotlib.

NMT for chinese-english using fairseq

Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

Tencent Social Ads 2017 contest rank 20

Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core

Links to Russian corpora + Python functions for loading and parsing

使用两种方法（抽取式Textrank和概要式seq2seq）自动提取文本摘要

A library to model multivariate data using copulas.

📚 专门为自然语言处理(NLP)面试准备的学习笔记与资料

2018达观杯长文本分类智能处理挑战赛 18解决方案

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

Tutorial and Examples Jupyter Notebooks for Altair

How to build RNNs and LSTMs from scratch with NumPy.

Multiscale Geographically Weighted Regression (MGWR)

Examples of using Raster Vision on open datasets

Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)

🎓 Tidy tools for academics

Mastering Python for Finance – Second Edition, published by Packt

Second edition of Springer Book Python for Probability, Statistics, and Machine Learning

DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)

Object detection and segmentation for a surgery robot using Mask-RCNN on Python 3, Keras, and TensorFlow..

Books Papers, Courses & more I have to learn soon

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

Important paper implementations for Question Answering using PyTorch

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

COMS W4995 Applied Machine Learning - Spring 18