Santiago Humberto Londoño Restrepo's repositories

CheckPronunciationFlask

Check Pronunciation is a tool that allow to evaluate pronunciation in Spanish Language

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UnitsTimePandasSeries

Python class that transforms a daily pandas series into pandas series with aggregated values depending on different units of time [weekly, monthly and yearly]

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catboost

CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R

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Cognitive-Speech-TTS

Microsoft Text-to-Speech API sample code in several languages, part of Cognitive Services.

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datathon

Solución al desafio educativo propuesto por Datathon-2017.

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ElectricityMarket-DataCamp

Code created to solve challenge sponsored by DataCamp, called: Understanding the Local Electricity Market

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Gender-gap-in-entrepreneurship

Gender gap in entrepreneurship is a web application for those interested in analyzing Global Entrepreneurship Monitor (GEM) data from a gender perspective.

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CompanyTests

Company tests that I have done to get a job

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datasciencectacontent

repository for Community Mentor content related to the Johns Hopkins University Data Science Specialization on Coursera

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docker-getting-started

Getting started with Docker

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lisa

Lisa: a spanish chatbot based on Deep Q&A, the implementation of "A neural conversational model"

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londoso.com

My personal website

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machine-learning-course

R code for the assignments of Coursera machine learning course

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myfirstmapLeaflet

Solution to the task of week 2 of the course Developing Data Products of the Johns Hopkins University offered through COURSERA.

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papershiny

Repositorio para el artículo

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PasosCrearRepo

Se describe el paso a paso y comandos git que uso frecuentemente para crear repositorios en sistemas de control de versiones.

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Pyutilities

Repositorio con pruebas de concepto sobre uso de librerías en el mundo python

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Robyn

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.

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Rutilities

Repositorio con pruebas de concepto sobre uso de librerías en el mundo R

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Testhff

To do post request in flask app deployed in heroku

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