This project combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
Copyright (c) 2021 Philip May
Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License by reviewing the file LICENSE in the repository.
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:
Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da
Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started
An open-source library of algorithms to analyse time series in GPU and CPU.
💯 Days of Machine Learning and Deep Learning Code MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Cluste
sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo
Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se
Demand-Forecasting Business Problem A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C
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
Cohort-Intelligence-for-Mathematical-Functions About Cohort Intelligence : Cohort Intelligence ( CI ) is an optimization technique. It attempts to mod
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 drif
AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast
Falken provides developers with a service that allows them to train AI that can play their games. Unlike traditional RL frameworks that learn through rewards or batches of offline training, Falken is
Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you
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