Python Machine Learning Resources

CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

YouTube Spam Detection This code deletes spam comment on youtube videos based on two characteristics (currently) If the author of the comment has a se

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

R-Solver A Python tools for deriving R-Type adaptors for Wave Digital Filters. This code is not quite production-ready. If you are interested in contr

This project shows steps to build an end to end MLOps architecture that covers data prep, model training, realtime and batch inference, build model registry, track lineage of artifacts and model drift detection. It utilizes SageMaker Pipelines that offers machine learning (ML) to orchestrate SageMaker jobs and author reproducible ML pipelines.

Simplify stop motion animation with machine learning.

mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Machine learning that just works, for effortless production applications

napari-sklearn-decomposition A simple plugin to use with napari This napari plug

Simple-Classifier This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example as

MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t

vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s

DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters

A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)

This project is a community effort in constructing and maintaining an up-to-date beginner-friendly introduction to AutoML, focusing on practical systems. AutoML is a big field, and continues to grow daily. Hence, we cannot hope to provide a comprehensive description of every interesting idea or approach available.

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod

Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

Toy implementations of some popular ML optimizers using Python/JAX

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

The Emergence of Individuality

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab

Send Rockets To Mars With AI Send rockets to Mars with artificial intelligence(Genetic algorithm) in python. Tools Python 3 EasyDraw How to Play Insta

Machine care An simple python script to take care of simple maintenance tasks fo

Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin

In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very lengthy and uncertain that most of the customers will buy it. So, there is a very need for a filtering system that segregates the customers who are unlikely to buy loans and the opposite. Loan-Web is visualized and made up on that context.

pyspark-anonymizer Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark envir

scikit-multimodallearn is a Python package implementing algorithms multimodal data. It is compatible with scikit-learn, a popul

Naive-Bayes Spam Classificator Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a

AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just

Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D

This repo implements a topological SLAM system. Deep Visual Odometry (DF-VO) and Visual Place Recognition are combined to form the topological SLAM system.

fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa

WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.

easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.

Time-series-momentum Time-series momentum strategy. You can use the data_analysis.py file to find out the best trigger and window for a given asset an

CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

torque_model The torque model is a spiritual successor to op-smart-torque, which was a project to train a neural network to control a car's steering f

mlflow-azurite-postgres docker This is a MLFLow image which works with a postgres DB and a local Azure Blob Storage Instance (Azurite). This image is

mastrade MasTrade is a trading bot in baselines3,pytorch,gym idea we have for example 1 btc and we buy a crypto with it with market option to trade in

PyHarmonize: Adding harmony lines to recorded melodies in Python About To use this module, the user provides a wav file containing a melody, the key i

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

pandas-method-chaining pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code. It is a fork from pandas-v

Summer: compartmental disease modelling in Python Summer is a Python-based framework for the creation and execution of compartmental (or "state-based"

Bayesian optimization in JAX

基于马尔可夫链的写作机器人 前端 用html/css完成 Demo展示（已给出文本的相应展示） 用户提供相关的语料库后训练的成果 后端 要完成的几个接口 解析文

AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p