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

Last update: May 24, 2022

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

Movie recommadation

Codebase structure

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

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

Owner

Ibrahim Koné

GitHub Repository

Probabilistic time series modeling in Python

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

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Implementation of deep learning models for time series in PyTorch.

List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

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Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

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

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Katana project is a template for ASAP 🚀 ML application deployment

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100 Dec 26, 2022

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

10 May 15, 2022

Simple data balancing baselines for worst-group-accuracy benchmarks.

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

29 Dec 02, 2022

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

1 Jan 11, 2022

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

Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast

2 Apr 18, 2022

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

176 Jan 04, 2023

moDel Agnostic Language for Exploration and eXplanation

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

1.2k Jan 04, 2023

Python Research Framework

106 Dec 13, 2022

Management of exclusive GPU access for distributed machine learning workloads

TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting

131 Dec 12, 2022

Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

216 Dec 23, 2022

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm

59 Dec 09, 2022

Bonsai: Gradient Boosted Trees + Bayesian Optimization

Bonsai is a wrapper for the XGBoost and Catboost model training pipelines that leverages Bayesian optimization for computationally efficient hyperparameter tuning.

24 Oct 27, 2022

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

129 Dec 24, 2022

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

366 Jan 03, 2023

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

Related tags

Overview

Author Ibrahim Koné

From-Machine-Learning-Models-To-WebAPI

Customer Churn Api

Movie recommadation

Codebase structure

Owner

Ibrahim Koné

Probabilistic time series modeling in Python

Implementation of deep learning models for time series in PyTorch.

Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Katana project is a template for ASAP 🚀 ML application deployment

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

Simple data balancing baselines for worst-group-accuracy benchmarks.

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

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

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

moDel Agnostic Language for Exploration and eXplanation

Python Research Framework

Management of exclusive GPU access for distributed machine learning workloads

Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

Bonsai: Gradient Boosted Trees + Bayesian Optimization

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Getting Profit and Loss Make Easy From Binance

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This repo implements a Topological SLAM: Deep Visual Odometry with Long Term Place Recognition (Loop Closure Detection)