376 Open source projects that are alternatives of or similar to Solar-Rad-Forecasting

Python package for early warning signals (EWS) of bifurcations in time series data.

TensorFlow Implementation of TCN (Temporal Convolutional Networks)

Hands-on in-person workshop for Deep Learning with TensorFlow

Das Nowcasting erstellt eine Schätzung des Verlaufs der Anzahl von bereits erfolgten SARS-CoV-2-Erkrankungsfällen in Deutschland unter Berücksichtigung des Diagnose-, Melde- und Übermittlungsverzugs.

Reusable CNN and RNN model doing time series binary classification

Tidy time series forecasting

TensorFlow-based implementation of "Attend, Infer, Repeat" paper (Eslami et al., 2016, arXiv:1603.08575).

A unified framework for machine learning with time series

sknifedatar is a package that serves primarily as an extension to the modeltime 📦 ecosystem. In addition to some functionalities of spatial data and visualization.

RNN(LSTM, GRU) in Theano with mini-batch training; character-level language models in Theano

IAM dataset

Project 4 for Metis bootcamp. Objective was generation of character-level RNN trained on Donald Trump's statements using Keras. Also generated Markov chains, and quick pyTorch RNN as baseline. Attempted semi-supervised GAN, but was unable to test in time.

No description or website provided.

机器学习、深度学习、NLP实战项目

Lisflood OS - LISFLOOD

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Implementation of a LSTM with TensorFlow and distributed on Apache Spark

📓 Notes for Andrew Ng's courses on deep learning

All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (3rd ed, 2020) by Rob J Hyndman and George Athanasopoulos <http://OTexts.org/fpp3/>. All packages required to run the examples are also loaded.

Dual-Stage Attention-Based Recurrent Neural Net for Time Series Prediction

The Electricity Transformer dataset is collected to support the further investigation on the long sequence forecasting problem.

Modeltime unlocks time series forecast models and machine learning in one framework

Time Series Ensemble Forecasting

Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.

The simplest machine learning library for launching UIs, running evaluations, and comparing model performance.

Extensive and accessible COVID-19 data + forecasting for counties and hospitals. 📈

Recurrent Additive Networks for Tensorflow

Programs for stock prediction and evaluation

Generating image captions using Xception Network and Beam Search in Keras

Probabilistic time series modeling in Python

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

Wayeb is a Complex Event Processing and Forecasting (CEP/F) engine written in Scala.

The implementation of LSTM in TensorFlow used for the stock prediction.

The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.

This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.

Deep learning for forecasting company fundamental data

Stock market forecasting using the ARIMA model.

A Python library for integrating model-based and judgmental forecasting

NeuralProphet - A simple forecasting model based on Neural Networks in PyTorch

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (3rd ed, 2020) by Rob J Hyndman and George Athanasopoulos <http://OTexts.org/fpp3/>. All packages required to run the examples are also loaded.

Python＆機械学習ライブラリ TensorFlow の使い方の練習コード集。特にニューラルネットワークを重点的に取り扱い。

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

PyForecast is a statistical modeling tool used by Reclamation water managers and reservoir operators to train and build predictive models for seasonal inflows and streamflows. PyForecast allows users to make current water-year forecasts using models developed with the program.

forecast package for R

Scalable machine 🤖 learning for time series forecasting.

Extrapolate gender from first names using Naïve-Bayes and PyTorch Char-RNN

ARCH models in Python

In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.

Kaggle | Web Traffic Forecasting 📈

SEIR+ model

RNN-LSTM that learns passwords from a starting list

A collection of awesome projects, blog posts, books, and talks on quantifying risk

Char RNN Language Model based on Tensorflow

Collection of custom layers and utility functions for Keras which are missing in the main framework.

Probabilistic Dialogue Act Classification for the Switchboard Corpus using an LSTM model

WATTNet: Learning to Trade FX with Hierarchical Spatio-Temporal Representations of Highly Multivariate Time Series

Personal Financial Forecasting Model

medium blog supplementaries | Backprop | Resnet & ResNext | RNN |

This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of predictions with modification suggested by Harvey et. al (1997).