ledmaster

gpt-summarizer

A scrappy Jupyter notebook to summarize long podcasts, youtube videos, etc

meli2020

9th (public) place solution to MeLi Data Challenge 2020

notebooks_tutoriais

Aqui você encontrar notebooks para alguns vídeos do meu canal no Youtube

swing

Implementation of the Swing Algorithm for Substitute Product Recommendation in Python

TimeSeriesForecasting

Material for the Time Series Forecasting article

TutorialEnsemble

Arquivos para o tutorial do artigo Tutorial: Aumentando o Poder Preditivo de Seus Modelos de Machine Learning com Stacking Ensembles

TutorialTitanic

tw-bert

Implementation of End-to-End Query Term Weighting (TW-BERT)

unified-embeddings

Implementation of Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

ledmaster/notebooks_tutoriais

Aqui você encontrar notebooks para alguns vídeos do meu canal no Youtube

ledmaster/TimeSeriesForecasting

Material for the Time Series Forecasting article

ledmaster/TutorialTitanic

ledmaster/gpt-summarizer

A scrappy Jupyter notebook to summarize long podcasts, youtube videos, etc

ledmaster/TutorialEnsemble

Arquivos para o tutorial do artigo Tutorial: Aumentando o Poder Preditivo de Seus Modelos de Machine Learning com Stacking Ensembles

ledmaster/meli2020

9th (public) place solution to MeLi Data Challenge 2020

ledmaster/tw-bert

Implementation of End-to-End Query Term Weighting (TW-BERT)

ledmaster/learningcandlesticks

http://mariofilho.com/can-machine-learning-model-predict-the-sp500-by-looking-at-candlesticks/

ledmaster/english_tutorials

ledmaster/recomendacaomachinelearning

Material do artigo: Como Criar um Sistema de Recomendação de Produtos Usando Machine Learning

ledmaster/machinelearninginadimplencia

Material do artigo: Será Que Seu Cliente Vai Te Pagar? Usando Machine Learning Para Prever Inadimplência

ledmaster/multiple_steps_neural_network

How To Use Neural Networks to Forecast Multiple Steps of a Time Series

ledmaster/unified-embeddings

Implementation of Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

ledmaster/clippy-adagrad

PyTorch Implementation of Improving Training Stability for Multitask Ranking Models in Recommender Systems

ledmaster/machine-learning-success

How did you successfully apply machine learning in a company? Here we share the impact that deployed machine learning systems made on business related metrics.

ledmaster/swing

Implementation of the Swing Algorithm for Substitute Product Recommendation in Python

ledmaster/AvitoSolution

Solução para a competição da Avito no Kaggle

ledmaster/Kaggle_CrowdFlower

1st Place Solution for Search Results Relevance Competition on Kaggle (https://www.kaggle.com/c/crowdflower-search-relevance)

ledmaster/TSPBrasil

Material sobre o artigo "Usando Otimização Para Aproximar a Menor Rota Entre Mais de 5.500 Municípios Brasileiros" publicado no site MarioFilho.com

ledmaster/xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

ledmaster/AvazuSolution

Material do artigo sobre a competição Avazu

ledmaster/CourseraCompDataAnalysis

Code for the course Computational Methods for Data Analysis on Coursera

ledmaster/ec2SpotPrices

Uses boto to retrieve current spot instance prices on Amazon EC2.

ledmaster/fixes

ledmaster/ledmaster

ledmaster/multiple_steps_neural

ledmaster/nolearn

scikit-learn compatible wrappers for neural net libraries, and other utilities.

ledmaster/numerapi

Python API and command line interface for the numer.ai machine learning competition

ledmaster/OnlineSVMPegasos

Code and dataset for the article on implementation of Online SVM using Pegasos

ledmaster/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 a