Collection of sports betting AI tools.

Overview

Travis Codecov CircleCI ReadTheDocs PythonVersion Pypi Conda

sports-betting

sports-betting is a collection of tools that makes it easy to create machine learning models for sports betting and evaluate their performance. It is compatible with scikit-learn.

Documentation

Installation documentation, API documentation, and examples can be found on the documentation.

Dependencies

sports-betting is tested to work under Python 3.6+. The dependencies are the following:

  • pandas(>=1.1.0)
  • rich(>=4.28)

Installation

sports-betting is currently available on the PyPi's repository and you can install it via pip:

pip install -U sports-betting

The package is released also in Anaconda Cloud platform:

conda install -c algowit sports-betting

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone https://github.com/AlgoWit/sports-betting.git
cd sports-betting
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/AlgoWit/sports-betting.git

Testing

After installation, you can use pytest to run the test suite:

make test
Owner
George Douzas
Physicist
George Douzas
The implementation of CVPR2021 paper Temporal Query Networks for Fine-grained Video Understanding, by Chuhan Zhang, Ankush Gupta and Andrew Zisserman.

Temporal Query Networks for Fine-grained Video Understanding đź“‹ This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

55 Dec 21, 2022
An image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testingAn image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testing

SVM Données Une base d’images contient 490 images pour l’apprentissage (400 voitures et 90 bateaux), et encore 21 images pour fait des tests. Prétrait

Achraf Rahouti 3 Nov 30, 2021
Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation"

Implicit-Semantic-Response-Alignment Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation" Prerequisites pyt

4 Dec 19, 2022
Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR)

This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.

Yongchun Zhu 81 Dec 29, 2022
Learning to Draw: Emergent Communication through Sketching

Learning to Draw: Emergent Communication through Sketching This is the official code for the paper "Learning to Draw: Emergent Communication through S

19 Jul 22, 2022
This program creates a formatted excel file which highlights the undervalued stock according to Graham's number.

Over-and-Undervalued-Stocks Of Nepse Using Graham's Number Scrap the latest data using different websites and creates a formatted excel file that high

6 May 03, 2022
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition

Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition Introduction Run attack: SGADV.py Objective function: foolbox/attacks/gradi

1 Jul 18, 2022
Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals"

The Temporal Robustness of Stochastic Signals Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals" Case stud

0 Oct 28, 2021
Fair Recommendation in Two-Sided Platforms

Fair Recommendation in Two-Sided Platforms

gourabgggg 1 Nov 10, 2021
Just Randoms Cats with python

Random-Cat Just Randoms Cats with python.

OriCode 2 Dec 21, 2021
Code for paper entitled "Improving Novelty Detection using the Reconstructions of Nearest Neighbours"

NLN: Nearest-Latent-Neighbours A repository containing the implementation of the paper entitled Improving Novelty Detection using the Reconstructions

Michael (Misha) Mesarcik 4 Dec 14, 2022
Official implementation for paper Render In-between: Motion Guided Video Synthesis for Action Interpolation

Render In-between: Motion Guided Video Synthesis for Action Interpolation [Paper] [Supp] [arXiv] [4min Video] This is the official Pytorch implementat

8 Oct 27, 2022
OpenMMLab Detection Toolbox and Benchmark

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

OpenMMLab 22.5k Jan 05, 2023
[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore

[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of

AccSrd 1 Sep 22, 2022
PRTR: Pose Recognition with Cascade Transformers

PRTR: Pose Recognition with Cascade Transformers Introduction This repository is the official implementation for Pose Recognition with Cascade Transfo

mlpc-ucsd 133 Dec 30, 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
An ML & Correlation platform for transforming disparate data points of interest into usable intelligence.

SSIDprobeCollector An ML & Correlation platform for transforming disparate data points of interest into usable intelligence. At a High level the platf

Bill Reyor 1 Jan 30, 2022
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention

E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G

Phil Wang 132 Jan 02, 2023
PyTorch implementation of SimSiam: Exploring Simple Siamese Representation Learning

SimSiam: Exploring Simple Siamese Representation Learning This is a PyTorch implementation of the SimSiam paper: @Article{chen2020simsiam, author =

Facebook Research 834 Dec 30, 2022
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022