Max Pumperla

Minimum description length principle algorithm in Python, for optimal binning of continuous variables

An independent implementation of DeepMind's AlphaGoZero in Scala, using Deeplearning4J (DL4J)

BetaGo: AlphaGo for the masses, live on GitHub.

Code and other material for the book "Deep Learning and the Game of Go"

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Notebooks for the O'Reilly book "Learning Ray"

Distributed Deep learning with Keras & Spark

Distributed Asynchronous Hyperparameter Optimization in Python

Time Series Prediction: A Non Linear Approach with Neural Networks

Public notebook for colab-hosted exercises for https://applied-rl-course.netlify.app/

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Sketching a Real-Time Analytics Pipeline in Python

Typer, build great CLIs. Easy to code. Based on Python type hints.

Cthulhu: Deep Learning for demons

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for testing only

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An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

A clean book theme for scientific explanations and documentation with Sphinx

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pyreadme - Python interface for the readme.io HTTP API

A tiny distributed neural network implementation based on micrograd and Ray

Binder dependencies for applied-rl-course.netlify.app

Skymind Test Resource Upload Management for Paunchy Files (STRUMPF)

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Factory solver implementation

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COVID-19 development gapminder visualisation

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