Machine-Learning with python (jupyter)

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Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

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Stats, linear algebra and einops for xarray

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This repo includes some graph-based CTR prediction models and other representative baselines.

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Self Organising Map (SOM) for clustering of atomistic samples through unsupervised learning.

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QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

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A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

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ETNA – time series forecasting framework

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Hierarchical Time Series Forecasting using Prophet

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A Lucid Framework for Transparent and Interpretable Machine Learning Models.

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Python library for multilinear algebra and tensor factorizations

scikit-tensor is a Python module for multilinear algebra and tensor factorizations

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ML-powered Loan-Marketer Customer Filtering Engine

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 length

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A simple machine learning python sign language detection project.

SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri

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Estudos e projetos feitos com PySpark.

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a distributed deep learning platform

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To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.

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Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics

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Machine-Learning with python (jupyter)

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Overview

Machine-Learning with python (jupyter)

들어가기전

머신 러닝 1

텐서플로

ETC

Owner

HyeonWoo Jeong

Projeto: Machine Learning: Linguagens de Programacao 2004-2001

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Stats, linear algebra and einops for xarray

This repo includes some graph-based CTR prediction models and other representative baselines.

Self Organising Map (SOM) for clustering of atomistic samples through unsupervised learning.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

A collection of Scikit-Learn compatible time series transformers and tools.

ETNA – time series forecasting framework

Hierarchical Time Series Forecasting using Prophet

A Lucid Framework for Transparent and Interpretable Machine Learning Models.

Python library for multilinear algebra and tensor factorizations

ML-powered Loan-Marketer Customer Filtering Engine

A simple machine learning python sign language detection project.

Estudos e projetos feitos com PySpark.

a distributed deep learning platform

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction

Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis.

Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill

[HELP REQUESTED] Generalized Additive Models in Python

DaCeML - Machine learning powered by data-centric parallel programming.