A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.

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Overview

Author Ibrahim Koné

From-Machine-Learning-Models-To-WebAPI

A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.



Customer Churn Api

App Video

Movie recommadation

App Video

Codebase structure

The project is coded using a simple and intuitive structure presented below:

< PROJECT ROOT >
   |
   |-- CustomerchurnAPI/                              
   |--Movierecommadation/
   |
   |-- ************************************************************************

Owner
Ibrahim Koné
Ibrahim Koné
GitHub Repository
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QML: A Python Toolkit for Quantum Machine Learning

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Projeto: Machine Learning: Linguagens de Programacao 2004-2001

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XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

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MICOM is a Python package for metabolic modeling of microbial communities

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FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically

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Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

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Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

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Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible

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Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

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