- managing folders of data
- saving experiments post-fact
- waiting for stuff to run
- easily seeing all your hyper-parameters
- working out what you've done before
- trying out different things, and saving them somehow
- debugging models
- wanting to visualise various outputs arbitrarily
- doing things with streaming data?
- loss landscape visualisation
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| {-# LAnguage FlexibleInstances #-} | |
| {-# LANGuage FunctionalDependencies #-} | |
| {-# LANGUAge GADTs #-} | |
| {-# LANGUAGE UndecidableInstances #-} | |
| module Trolling where | |
| --------------------------------------------------------------------- | |
| -- VARIADIC COMPOSITION IN HASKELL (A LA RAMDA.JS). | |
| -- | |
| -- In Haskell, we typeically think of the composition operator (or |
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| # a simple dashboard for the waveshare 2in7b screen | |
| # to be ran inside: https://github.com/waveshare/e-Paper/tree/master/RaspberryPi%26JetsonNano/python/examples | |
| # 1. install the latest versions of `pyowm` and `requests` | |
| # 2. edit `OPEN_WEATHER_KEY`, `LOCATION`, and `NEWS_API_KEY` | |
| import sys | |
| import os | |
| picdir = os.path.join(os.path.dirname(os.path.dirname(os.path.realpath(__file__))), 'pic') | |
| libdir = os.path.join(os.path.dirname(os.path.dirname(os.path.realpath(__file__))), 'lib') | |
| if os.path.exists(libdir): |
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| from collections import Counter | |
| from fractions import Fraction | |
| def _gcd(a, b): | |
| while a: | |
| a, b = b % a, a | |
| return b | |
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| {-# LANGUAGE TupleSections #-} | |
| module Main where | |
| import Graphics.Gloss | |
| import Graphics.Gloss.Raster.Field | |
| import System.Random | |
| import Data.Semigroup | |
| import GHC.Base (NonEmpty(..)) |
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| {-# LANGUAGE TupleSections #-} | |
| module Main where | |
| import Graphics.Gloss | |
| import Graphics.Gloss.Raster.Field | |
| import System.Random | |
| import Data.Semigroup | |
| import GHC.Base (NonEmpty(..)) |
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| // http://journal.stuffwithstuff.com/2013/12/08/babys-first-garbage-collector/ | |
| // | |
| #define STACK_MAX 256 | |
| #define INITIAL_GC_THRESHOLD 2 | |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| void gc(); // Pre-Declared for co-recursive usage |
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| """ | |
| Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you | |
| run simple training experiments for NER and text classification. | |
| Requires the Prodigy annotation tool to be installed: https://prodi.gy | |
| See here for details on Streamlit: https://streamlit.io. | |
| """ | |
| import streamlit as st | |
| from prodigy.components.db import connect | |
| from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size |
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| """ | |
| Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you | |
| run simple training experiments for NER and text classification. | |
| Requires the Prodigy annotation tool to be installed: https://prodi.gy | |
| See here for details on Streamlit: https://streamlit.io. | |
| """ | |
| import streamlit as st | |
| from prodigy.components.db import connect | |
| from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size |
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| pip install streamlit | |
| pip install spacy | |
| python -m spacy download en_core_web_sm | |
| python -m spacy download en_core_web_md | |
| python -m spacy download de_core_news_sm |