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
Neural Scene Graphs for Dynamic Scene (CVPR 2021)

Implementation of Neural Scene Graphs, that optimizes multiple radiance fields to represent different objects and a static scene background. Learned representations can be rendered with novel object

151 Dec 26, 2022
The official implementation of NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021]. https://arxiv.org/pdf/2101.12378.pdf

NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021] Release Notes The offical PyTorch implementation of NeMo, p

Angtian Wang 76 Nov 23, 2022
Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at [email protected]

TableParser Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at DS3 Lab 11 Dec 13, 2022

StableSims is an open-source project aimed at simulating MakerDAO's Dai stablecoin system

StableSims is an open-source project aimed at simulating MakerDAO's Dai stablecoin system, initially used for researching optimal incentive parameters for Liquidations 2.0.

Blockchain at Berkeley 52 Nov 21, 2022
Yolo Traffic Light Detection With Python

Yolo-Traffic-Light-Detection This project is based on detecting the Traffic light. Pretained data is used. This application entertained both real time

Ananta Raj Pant 2 Aug 08, 2022
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav

Jakob Aungiers 4.1k Jan 02, 2023
Fine-Tune EleutherAI GPT-Neo to Generate Netflix Movie Descriptions in Only 47 Lines of Code Using Hugginface And DeepSpeed

GPT-Neo-2.7B Fine-Tuning Example Using HuggingFace & DeepSpeed Installation cd venv/bin ./pip install -r ../../requirements.txt ./pip install deepspe

Nikita 180 Jan 05, 2023
The code for paper Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation Algorithm

Quantum Qubit Rotation Algorithm Single qubit rotation gates $$ U(\Theta)=\bigotimes_{i=1}^n R_x (\phi_i) $$ QQRA for the max-cut problem This code wa

SheffieldWang 0 Oct 18, 2021
Trajectory Extraction of road users via Traffic Camera

Traffic Monitoring Citation The associated paper for this project will be published here as soon as possible. When using this software, please cite th

Julian Strosahl 14 Dec 17, 2022
DCA - Official Python implementation of Delaunay Component Analysis algorithm

Delaunay Component Analysis (DCA) Official Python implementation of the Delaunay

Petra Poklukar 9 Sep 06, 2022
Vehicle Detection Using Deep Learning and YOLO Algorithm

VehicleDetection Vehicle Detection Using Deep Learning and YOLO Algorithm Dataset take or find vehicle images for create a special dataset for fine-tu

Maryam Boneh 96 Jan 05, 2023
Generating Fractals on Starknet with Cairo

StarknetFractals Generating the mandelbrot set on Starknet Current Implementation generates 1 pixel of the fractal per call(). It takes a few minutes

Orland0x 10 Jul 16, 2022
Pointer-generator - Code for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Networks

Note: this code is no longer actively maintained. However, feel free to use the Issues section to discuss the code with other users. Some users have u

Abi See 2.1k Jan 04, 2023
This is an official implementation for "ResT: An Efficient Transformer for Visual Recognition".

ResT By Qing-Long Zhang and Yu-Bin Yang [State Key Laboratory for Novel Software Technology at Nanjing University] This repo is the official implement

zhql 222 Dec 13, 2022
DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

Facebook Research 145 Dec 30, 2022
SPRING is a seq2seq model for Text-to-AMR and AMR-to-Text (AAAI2021).

SPRING This is the repo for SPRING (Symmetric ParsIng aNd Generation), a novel approach to semantic parsing and generation, presented at AAAI 2021. Wi

Sapienza NLP group 98 Dec 21, 2022
African language Speech Recognition - Speech-to-Text

Swahili-Speech-To-Text Table of Contents Swahili-Speech-To-Text Overview Scenario Approach Project Structure data: models: notebooks: scripts tests: l

2 Jan 05, 2023
Repository for publicly available deep learning models developed in Rosetta community

trRosetta2 This package contains deep learning models and related scripts used by Baker group in CASP14. Installation Linux/Mac clone the package git

81 Dec 29, 2022
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple

Haochen Wang 268 Dec 24, 2022
This is the pytorch re-implementation of the IterNorm

IterNorm-pytorch Pytorch reimplementation of the IterNorm methods, which is described in the following paper: Iterative Normalization: Beyond Standard

Lei Huang 32 Dec 27, 2022