- on lion (and snow leopard i suppose), make sure you are using a 64 bit install of ghc. Also, unless you are suggesting an edit to these directions, please go ask people on the relevant mailing list or wiki for help :)
- Tested on Mac OS X 10.7.4, GHC 7.4.1, 64bit Haskell Platform 2012.2.0.0 (installer package) with Command Line Tools for XCode (June 2012).
- These notes were originally brought to you by Carter Schonwald; the “I” probably refers to him. Eric Kow will refer to himself in the third person).
- Forked from kowey (Eric Kow): https://gist.github.com/2420144
Jonathan Jouty jonathanjouty
jonathanjouty
/ gist:3086205
Created
July 10, 2012 21:01
— forked from kowey/gist:2420144
Haskell GTK on 64 bit MacOS X
jonathanjouty
/ installing-ghc7.6.1-osx10.8.md
Created
October 17, 2012 11:24
— forked from beastaugh/installing-ghc7.2-osx10.7.md
Installing GHC 7.6.1 on Mac OS X 10.8 Mountain Lion
This is a brief and bare-bones guide to getting GHC 7.6.1 and the cabal-install
tool (the two basic things you'll need to do Haskell development) up and running
on Mac OS X 10.8 install.
The instructions given here worked for me, but YMMV.
Original on https://gist.github.com/1169332
jonathanjouty
/ simple_rnn_mnist.py
Created
March 5, 2017 20:40
— forked from LazarValkov/simple_rnn_mnist.py
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| ''' | |
| A Recurrent Neural Network (LSTM) implementation example using TensorFlow library. | |
| This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/) | |
| Long Short Term Memory paper: http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf | |
| Author: Aymeric Damien | |
| Project: https://github.com/aymericdamien/TensorFlow-Examples/ | |
| ''' | |
| from __future__ import print_function |
jonathanjouty
/ lofp.md
Last active
December 11, 2020 14:03
— forked from chris-martin/lofp.md
http://lambdaconf.us/downloads/documents/lambdaconf_slfp.pdf
The LambdaConf Ladder of Functional Programming (LOFP) is a standardized progression of different concepts and skills that developers must master on their journey to becoming expert-level functional programmers. LOFP can be used to rank workshops, talks, presentations, books, and courseware, so that aspiring functional programmers have a better understanding of what material is appropriate for them given their current experience.
- Immutable Data
- Second-order Functions