Search Results for "neural net time series"
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Showing 37 open source projects for "neural net time series"
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock prices... -
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along... -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can... -
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T81 558
Applications of Deep Neural Networks
... structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in doubt... -
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gulp
A toolkit to automate & enhance your workflow
gulp is a streaming build system that automates slow, repetitive and time-consuming tasks in your development workflow. It is simple and easy to use with only a minimal API surface, but powerful enough to compose efficient build pipelines. gulp is flexible and composable, and is also platform-agnostic, which means you can use it with PHP, .NET, Java and many other platforms. It’s got a strong ecosystem of npm modules and over 3000 curated, community-built plugins, so you can achieve exactly... -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
... brush up on your knowledge. The pre-reqs refresher days are asynchronous, so you can go through the material on your own time. You will learn how to code in Python from scratch using a simple neural model, the leaky integrate-and-fire model, as a motivation. Then, you will cover linear algebra, calculus and probability & statistics. The topics covered on these days were carefully chosen based on what you need for the comp neuro course. -
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DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
... of image tagging, object detection, segmentation, OCR, Audio, Video, Text classification, CSV for tabular data and time series. Neural network templates for the most effective architectures for GPU, CPU, and Embedded devices. Training in a few hours and with small data thanks to 25+ pre-trained models. Full Open Source, with an ecosystem of tools (API clients, video, annotation, ...) Fast Server written in pure C++, a single codebase for Cloud, Desktop & Embedded. -
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Auto-PyTorch
Automatic architecture search and hyperparameter optimization
While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, another trend in AutoML is to focus on neural architecture search. To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series data... -
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digiCamControl
Free camera control solution
digiCamControl is an free and open source software. This allows you to save time by transferring images directly from your camera to your computer as you take each shot and allow to control camera shooting parameters. -
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Data augmentation
List of useful data augmentation resources
.../landmarks Augmentation, usually done with image augmentation (rotation, reflection) or graph augmentation methods (node/edge dropping) Spectrograms/Melspectrograms, usually done with time series data augmentation (jittering, perturbing, warping) or image augmentation (random erasing) -
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Macbuntu BIGSur 2021
Macbuntu BIGSur 2021.6 x64 bit Kernel 5.11.18 on xubuntu lts 21.04
... screens have been changed using plymouth macosx files. Neofetch distro name changed to Macbuntu, Apple logo fixed default Old kernel files and remnants were cleaned, new modified kernel was applied up-to-date and fast attack MacOS BigSUR Icon and Theme packages Shell plugins are integrated into the pure state of the system. Xubuntu 21.04 LTS is a long-term support distribution. Continuous security updates and support works that take a long time until 2023 are preferred in this context. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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SwaNN
PSO for neural networks
SwaNN is a basic framework for neural networks based on particle swarm optimization (using the Python package PySwarms (https://pyswarms.readthedocs.io/en/latest/). The zip file contains the main programs in SwaNN.py and around 30 examples : - classification - regression - time series forecasting I need some help for class building (I am not an expert in Python nor in OOP), if somebody is interested in it... In Google Colab : https://colab.research.google.com/drive... -
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WDTVHubGen2
Searching metada for your Video Files and renaming them properly
******WDTVHubGen2 is no more working since July 2022********** WDTVHubGen2 is a batch processor for getting metadata and thumbs for a wdtv live hub. processes both movies and tv shows, supports many languages and uses themoviedb.org and thetvdb.com. This program also does a lot of parsing to make the files easier to lookup and even aggressively looks up filenames where there are download tags and such. Simply download the latest build und unzip. It will probably need .Net Framework... -
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Tsf_Mdnnhn
Time Series Forecasting.
Implementation of algorithm allowing Time Series Forecasting. -
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DSTK - Data Science TooKit 3
Data and Text Mining Software for Everyone
DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI... -
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DBPlot (DataPlot, DatabasePlot, CsvPlot)
Plot your data in seconds (MsSQL, MySQL, PostgreSQL, SQLite, CSV)
A great tool to quickly visualize data. DBPlot supports MsSQL, MySQL, PostgreSQL, SQLite, and CSV files with drag-drop and data type inference capabilities. -
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NARX simulator with neural networks
A simulator for NARX ( Nonlinear AutoRegressive with eXogenous inputs)
This projects aims at creating a simulator for the NARX (Nonlinear AutoRegressive with eXogenous inputs ) architecture with neural networks. The system can fallback to MLP ( multi layer perceptron ), TDNN ( time delay neural network ), BPTT ( backpropagation through time ) and a full NARX architecture. The system is intended to be used as a time series forecaster for educational purposes. This projects is my personal master thesis developed at the Master of Artificial Intelligence... -
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Lottery A.I.
Uses weights created by winning lottery numbers to predict the future
This program takes the oldest winning lottery numbers to the newest winning lottery numbers entered by the user to create a data base to predict the future winning lottery number. First time I used it I won money. -
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Swift Auto Mouse Click 1.1.2
Auto clicker capable of powerful and easy mouse automation
Use Swift AutoClick to define a mouse action or series of mouse actions that you can run on command with a hotkey. Set global custom hotkeys to start or stop your clicks anytime the application is open. After creating your instructions, you can save it, load it later or even edit the raw text file. Great for rapidly clicking and automating games or tedious applications. Also useful if you want to keep your computer, or any applications from sleeping or going AFK. This is an auto... -
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Gekko Timeseries Software
Timeseries handling, and solving of large-scale economic models
Gekko Timeseries Software is a free time-series oriented software package for timeseries handling, and solving and analyzing large-scale economic models. Since 2009, Gekko is being used by Danish ministeries, banks, interest groups and universities, for the simulation of economic and energy-related models. The software runs under Windows (.NET), and is open source (GNU GPL) -
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Neural Libs
Neural network library for developers
This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network. -
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Shawn's AutoCAD Scripter
AutoCAD batch scripting
... be done in parallel, so multiple drawings are being scripted at the same time. This feature is limited to splitting jobs based on directory, so scripting drawings in 5 directories would run 5 console instances. -
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This project is intending to build large-scale distributed Neural Networks, which can be used for time-series pattern recognition including but not limited to languages, images, music and videos.