Christopher Bare (cbare)

cbare

Geek Repo

Location:Wellington, New Zealand

Home Page:https://cbare.github.io/

Twitter:@christopherbare

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Organizations
baliga-lab
codeforsystemsbiology

Christopher Bare's repositories

Etudes

A collection of programming problems for learning new languages and practicing coding chops.

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cbare.github.io

J. Christopher Bare, software engineer and occasional writer

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fooalicious

Learn git in thousands of tricky and confusing steps

hackalicious

A repo for playing with Git

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Pydoku

Sudoku solver in python

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synapsePythonClient

Programmatic interface to Synapse services for Python. Please visit https://synapse.sagebase.org/ for more information.

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Jazzopedia

Music geekery and exploration of classic Jazz

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notes-on-deep-learning

Exercises in NNs and Deep Learning

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advent-of-code-2020

My solutions to Advent of Code 2020.

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cbare

Config files for my GitHub profile.

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connect-four

An api for playing the game connect-four.

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diffusion-nbs-fork

Getting started with diffusion

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dlaicourse

Notebooks for learning deep learning

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doccano

Open source text annotation tool for machine learning practitioner.

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dot-files

dot files

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fastai-class

Working through the fast ai class 2022 edition

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flhaskell

Functional Programming in Haskell class

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HelloDotNet

A test project to learn the basics of C# programming, very reluctantly.

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Intro_BayesReg

Repository for eScience seminar - A Practical Introduction to Bayesian Regression Analysis

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library-app

A toy project for learning React, context, and typescript.

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nlp-play

Playing with NLP

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papers

A place to put old papers.

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playing-with-llms

Playing with LLMs

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pubmed_miner

A demo on retrieving and clustering pubmed abstracts

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pydata2021-eda

[PyData Global 2021] Know Your Data First: An Introduction to Exploratory Data Analysis

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python_machine_learning_book

Code from or inspired by the book “Python Machine Learning”

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smart_open

Utils for streaming large files (S3, HDFS, gzip, bz2...)

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SynapseChallengeTemplates

A collection of templates for use by those writing Synapse challenge scoring applications. The aim is to provide executable examples in various languages (Python, R, Java).

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