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)
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions

Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI

Computational Biology and Machine Learning lab @ TOBB ETU 3 Oct 18, 2022
Predictive Maintenance LSTM

Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.

Amir M. Sadafi 1 Dec 31, 2021
Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

Raschka Research Group 14 Dec 27, 2022
Official codebase for Pretrained Transformers as Universal Computation Engines.

universal-computation Overview Official codebase for Pretrained Transformers as Universal Computation Engines. Contains demo notebook and scripts to r

Kevin Lu 210 Dec 28, 2022
Denoising images with Fourier Ring Correlation loss

Denoising images with Fourier Ring Correlation loss The python code accompanies the working manuscript Image quality measurements and denoising using

2 Mar 12, 2022
Official implementation for (Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation, CVPR-2021)

FRSKD Official implementation for Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation (CVPR-2021) Requirements Pytho

75 Dec 28, 2022
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

Yasunori Shimura 7 Oct 31, 2022
Code for NeurIPS2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints"

This repository is the code for NeurIPS 2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints". Edit 2021/

10 Dec 20, 2022
Source code for our paper "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations"

Source code for our paper "Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations" this repository is maintained by bo

Yuhan Liu 24 Nov 29, 2022
A large-scale database for graph representation learning

A large-scale database for graph representation learning

Scott Freitas 29 Nov 25, 2022
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

Tom-R.T.Kvalvaag 2 Dec 17, 2021
A time series processing library

Timeseria Timeseria is a time series processing library which aims at making it easy to handle time series data and to build statistical and machine l

Stefano Alberto Russo 11 Aug 08, 2022
SelfAugment extends MoCo to include automatic unsupervised augmentation selection.

SelfAugment extends MoCo to include automatic unsupervised augmentation selection. In addition, we've included the ability to pretrain on several new datasets and included a wandb integration.

Colorado Reed 24 Oct 26, 2022
This repository contains the code and models necessary to replicate the results of paper: How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M

OPTML Group 2 Oct 05, 2022
TensorFlow-based implementation of "Pyramid Scene Parsing Network".

PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo

HsuanKung Yang 323 Dec 20, 2022
Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

47 Jun 30, 2022
Robotic Process Automation in Windows and Linux by using Driagrams.net BPMN diagrams.

BPMN_RPA Robotic Process Automation in Windows and Linux by using BPMN diagrams. With this Framework you can draw Business Process Model Notation base

23 Dec 14, 2022
Affine / perspective transformation in Pose Estimation with Tensorflow 2

Pose Transformation Affine / Perspective transformation in Pose Estimation with Tensorflow 2 Introduction 이 repo는 pose estimation을 연구하고 개발하는 데 도움이 되기

Kim Junho 1 Dec 22, 2021
Use unsupervised and supervised learning to predict stocks

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

Vivek Palaniappan 1.5k Jan 06, 2023
Gray Zone Assessment

Gray Zone Assessment Get started Clone github repository git clone https://github.com/andreanne-lemay/gray_zone_assessment.git Build docker image dock

1 Jan 08, 2022