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If you are wondering where the data of this site comes from, please visit https://api.github.com/users/StrikingLoo/events. GitMemory does not store any data, but only uses NGINX to cache data for a period of time. The idea behind GitMemory is simply to give users a better reading experience.
Luciano StrikingLoo Buenos Aires medium.com/@strikingloo Computer Science student at University of Buenos Aires. Read my articles on medium.com/@strikingloo

StrikingLoo/dask-dataframe-benchmarking 26

A Jupyter Notebook I made to try out dask's Dataframes

StrikingLoo/AutoEncatter 8

An AutoEncoder using TensorFlow's Eager API to compress pictures of kittens.

StrikingLoo/average-char 6

Uses SIMD SSE instructions to find the average value of chars in a string

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Markov Chain based on the ASOIAF books

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Repo para la Hackatón del CECEN 2017

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An example repository for people to make test contributions.

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A JavaScript based CYOA Engine

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Convolutional Neural Network that classifies images of animals.

PR opened axelsavizky/music-generator

Changes
  • Agrego soporte para levantar archivos en multiproceso. Levanta 1024 archivos de gwern en 15 minutos usando 32 threads en una maquina de 16 cores. Recomiendo usar CORES*2 threads, pero pueden probar otras configuraciones.
  • Agrego modelo entrenado con 512 midis del dataset
  • Agrego otro modelo, entrenado con 1024 midis por 50 epochs (9hs para …converger). Alcanza loss 2.54 en dataset de test. La música que genera es ligeramente mejor en mi opinion pero no tenemos una forma buena de medir esto.

Siguientes cosas a agregar, en mi opinion:

  • Agregar soporte de sampleo usando beam search en vez de greedy (most likely note every time). Esto probablemente mejore la calidad de la musica compuesta
  • Agregar alguna metrica que no sea solo la val_loss, si es que encontramos alguna?
  • Probar otras arquitecturas (hyperparameter research, cosas como cambiar el dropout, agregar mas filtros o menos, agregar mas neuronas a la capa FC del final)
  • Finalmente, si alguno se la banca, ejecutarlo con TODO el dataset y no 1024 archivos (tenemos 77k para usar!). Me intriga ver si lograremos mejor loss y como cambia la calidad, pero en mi maquina local no da la infra creo.

Opcionalmente, me pregunto si llevar el codigo que levanta archivos y entrena un modelo a un script en vez de notebook lo hara ir mas rapido o no, la verdad que no se. Quizas compilandolo, pero ya ahi hago agua, si alguno quiere probarlo podemos agregarlo como experimento.

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PR opened boyter/boyter.org

small typo corrections in bloomfilter post

Hi there! I read your article on bloomfilters after seeing the link in HackerNews. I loved it! And I only had a vague idea of what bloomfilters were before reading it, so it was very helpful. But it had a few typos and weird wordings, and I'm pretty sure you wrote OR where you wanted to write AND. I took the liberty of correcting those bits (see what I did there?) and creating this PR. Feel free to merge it, review it or apply the changes yourself if you don't want me to appear as a collaborator. Loving your site, I'll probably check other articles soon!

Have a nice day, Lu

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small typo corrections in bloomfilter post Hi there! I read your article on bloomfilters after seeing the link in HackerNews. I loved it! And I only had a vague idea of what bloomfilters were before reading it, so it was very helpful. But it had a few typos and weird wordings, and I'm pretty sure you wrote OR where you wanted to write AND. I took the liberty of correcting those bits (see what I did there?) and creating this PR. Feel free to merge it, review it or apply the changes yourself if you don't want me to appear as a collaborator. Loving your site, I'll probably check other articles soon! Have a nice day, Lu

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