Contra is a lightweight, production ready Tensorflow alternative for solving time series prediction challenges with AI

Overview

GitHub contributors GitHub forks GitHub watchers GitHub stars GitHub issues MIT license


Logo

Contra AI Engine

A lightweight, production ready Tensorflow alternative developed by Styvio
styvio.com »

How to Use · Report Bug · Request Feature

Table of Contents
  1. About Contra
  2. Getting Started
  3. PyPi Module Page
  4. License
  5. Contact

About The Project

Welcome to Contra, a fully open source AI engine developed by Styvio. Contra is a lightweight, production ready alternative to Tensorflow. Contra is written fully in Python and built to solve complex problems with AI. Contra is built specifically to solve time series prediction problems, server or client side.

What is Contra?

Contra is a collections of functions that allow you to solve complex time series problems with AI. If you have used or built or used prediction algorithms before, you will fully understand what is going on under the hood here. Contra is based on the simple KNN algorithm, but with one major modification. Instead of averaging the closest data points, the prediction is based on a linear combination of the sum of all other previous outcomes, and their distance to the requested prediction in terms of their step function.

Why does Contra exist?

Other AI engines or libraries can sometimes take minutes to run, and produce weights files that are far to large to run directly on a production website. It is frusterating having to perform complex calculations off-server and then to sending the results over to a database via an API. It is equally frusterating having weights files that are over 0.5 GB large. These challenges make libraries like Tensorflow useless in solving complex problems fast. Using tensorflow for time series prediction is like attatching a V8 engine to a lawn mower. We have become far too farmiliar with these challenges, and built Contra to erase this headache.

How can I use Contra?

You can use Contra anywhere you need to solve a complex problem with AI. Contra can be applied anywhere annalysis of time series data using AI prediction makes sense. Contra comes with the MIT liscence, meaning you can use it for personal and commercial projects without worying about liscence fees, giving credit, or litigation.

Getting Started

This section provides assistance on how to install Contra, as well as a general rundown on using the module.

Installation

pip install Contra (coming soon)

Quickstart

Now that the Contra module is installed, it can be imported in any .py python file, wherever you normally write code.

You might also like...
FwordCTF 2021 Infrastructure and Source code of Web/Bash challenges

FwordCTF 2021 You can find here the source code of the challenges I wrote (Web and Bash) in FwordCTF 2021 and the source code of the platform with our

Writeups for the challenges from DownUnderCTF 2021

cloud Challenge Author Difficulty Release Round Bad Bucket Blue Alder easy round 1 Not as Bad Bucket Blue Alder easy round 1 Lost n Found Blue Alder m

CTF challenges and write-ups for MicroCTF 2021.

MicroCTF 2021 Qualifications About This repository contains CTF challenges and official write-ups for MicroCTF 2021 Qualifications. License Distribute

Code for all the Advent of Code'21 challenges mostly written in python

Advent of Code 21 Code for all the Advent of Code'21 challenges mostly written in python. They are not necessarily the best or fastest solutions but j

A python script to dump all the challenges locally of a CTFd-based Capture the Flag.
A python script to dump all the challenges locally of a CTFd-based Capture the Flag.

A python script to dump all the challenges locally of a CTFd-based Capture the Flag. Features Connects and logins to a remote CTFd instance. Dumps all

Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.
Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

Doge-Prediction - Coding Club prediction ig

Doge-Prediction Coding Club prediction ig Basically: Create an application that

PyArmadillo: an alternative approach to linear algebra in Python

PyArmadillo is a linear algebra library for the Python language, with an emphasis on ease of use.

A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection
A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection 1. 介绍 用以替代 NMS,在所有 bbox 中挑选出最优的集合。 NMS 仅考虑了 bbox 的得分,然后根据 IOU 来

Releases(PublicRelease)
[CVPR2021] The source code for our paper 《Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning》.

TBE The source code for our paper "Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Le

Jinpeng Wang 150 Dec 28, 2022
Baselines for TrajNet++

TrajNet++ : The Trajectory Forecasting Framework PyTorch implementation of Human Trajectory Forecasting in Crowds: A Deep Learning Perspective TrajNet

VITA lab at EPFL 183 Jan 05, 2023
[IROS'21] SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning

SurRoL IROS 2021 SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning Features dVRK compati

<a href=[email protected]"> 55 Jan 03, 2023
Pytorch implementation of paper: "NeurMiPs: Neural Mixture of Planar Experts for View Synthesis"

NeurMips: Neural Mixture of Planar Experts for View Synthesis This is the official repo for PyTorch implementation of paper "NeurMips: Neural Mixture

James Lin 101 Dec 13, 2022
iNAS: Integral NAS for Device-Aware Salient Object Detection

iNAS: Integral NAS for Device-Aware Salient Object Detection Introduction Integral search design (jointly consider backbone/head structures, design/de

顾宇超 77 Dec 02, 2022
social humanoid robots with GPGPU and IoT

Social humanoid robots with GPGPU and IoT Social humanoid robots with GPGPU and IoT Paper Authors Mohsen Jafarzadeh, Stephen Brooks, Shimeng Yu, Balak

0 Jan 07, 2022
RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering Authors: Xi Ye, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou and

Salesforce 72 Dec 05, 2022
A Framework for Encrypted Machine Learning in TensorFlow

TF Encrypted is a framework for encrypted machine learning in TensorFlow. It looks and feels like TensorFlow, taking advantage of the ease-of-use of t

TF Encrypted 0 Jul 06, 2022
The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network.

UNet-SIDE The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network. For Super Reso

TIANTIAN XU 1 Jan 13, 2022
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.

collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do

ShopRunner 96 Dec 29, 2022
ICLR21 Tent: Fully Test-Time Adaptation by Entropy Minimization

⛺️ Tent: Fully Test-Time Adaptation by Entropy Minimization This is the official project repository for Tent: Fully-Test Time Adaptation by Entropy Mi

Dequan Wang 204 Dec 25, 2022
moving object detection for satellite videos.

DSFNet: Dynamic and Static Fusion Network for Moving Object Detection in Satellite Videos Algorithm Introduction DSFNet: Dynamic and Static Fusion Net

xiaochao 39 Dec 16, 2022
Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model

Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model. Designed sample dashboard with insights and recommendation for

Yash 2 Apr 07, 2022
How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

EV-charging-impact This repository contains the code that has been used for the Queue modelling for the paper "How will electric vehicles affect traff

7 Nov 30, 2022
An implementation of a sequence to sequence neural network using an encoder-decoder

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

Luke Tonin 195 Dec 17, 2022
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L

Facebook Research 281 Dec 22, 2022
Pytorch version of VidLanKD: Improving Language Understanding viaVideo-Distilled Knowledge Transfer

VidLanKD Implementation of VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer by Zineng Tang, Jaemin Cho, Hao Tan, Mohi

Zineng Tang 54 Dec 20, 2022
Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxiv.org/abs/2108.09084).

Fastformer-Keras Unofficial Tensorflow-Keras implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Tensorflo

Yam Peleg 10 Jan 30, 2022
Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch

NÜWA - Pytorch (wip) Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch. This repository will be popul

Phil Wang 463 Dec 28, 2022
NAS-FCOS: Fast Neural Architecture Search for Object Detection (CVPR 2020)

NAS-FCOS: Fast Neural Architecture Search for Object Detection This project hosts the train and inference code with pretrained model for implementing

Ning Wang 180 Dec 06, 2022