Manikandan Sivanesan` manisnesan

Benchmarks

Natural Language Understanding Systems

GLUE : General Language Understanding Evaluation (GLUE) benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems. This is a benchmark of nine sentence- or sentence-pair language understanding tasks.

Multitask Challenge for NLP

decaNLP: Natural Language Decathlon, a new benchmark for studying general NLP models that can perform a variety of complex, natural language tasks. By requiring a single system to perform ten disparate natural language tasks, decaNLP offers a unique setting for multitask, transfer, and continual learning.

MLOps Basics

Configurations

Use Hydra to add configurations to python code.
Loading a simple config(yaml) file using OmegaConf and Hydra
Overriding configurations at runtime
Splitting the configuration across multiple files
Variable Interpolation
How to run the model with different parameter combinations

put #hide at the top of any cell you want to completely hide in the docs
put #hide_input at the top of a cell if you don't want code to be shown in the docs
cells containing #export or show_doc have their code hidden automatically
put #hide_output at the top of a cell if you don't want output to be shown in the docs
use #collapse_input or #collapse_output to include code or output in the docs under a collapsable element

(fastchai)  ~/0fastai/nbdev   master  make test
nbdev_test_nbs --flags ''
testing /home/msivanes/0fastai/nbdev/nbs/00_export.ipynb
Error in /home/msivanes/0fastai/nbdev/nbs/00_export.ipynb:
preprocess() missing 1 required positional argument: 'resources'
testing /home/msivanes/0fastai/nbdev/nbs/02_showdoc.ipynb
Error in /home/msivanes/0fastai/nbdev/nbs/02_showdoc.ipynb:
preprocess() missing 1 required positional argument: 'resources'
testing /home/msivanes/0fastai/nbdev/nbs/03_export2html.ipynb

	# Source: https://towardsdatascience.com/chi-squared-tests-to-compare-two-machine-learning-models-and-determine-whether-they-are-random-2a405fc55181
	import numpy as np
	import pandas as pd
	from scipy.stats import chi2_contingency
	data=[[58,7],[11,24]] #Model M1 table
	#Chi square statistic,pvalue,DOF,expected table
	stat, p, dof, expected = chi2_contingency(data)
	print('Chi-square statistic=',stat)
	print('Pvalue=',p)
	alpha=0.05

	─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
	poetry run pytest --no-cov
	============================================================================================================ test session starts ============================================================================================================
	platform linux -- Python 3.8.6, pytest-6.2.1, py-1.10.0, pluggy-0.13.1
	rootdir: /home/msivanes/0Work/routing/language-detection
	plugins: cov-2.10.1
	collected 14 items / 1 error / 13 selected

	================================================================================================================== ERRORS =============

	General principles for good URI design:

	Don't use query parameters to alter state
	Don't use mixed-case paths if you can help it; lowercase is best
	Don't use implementation-specific extensions in your URIs (.php, .py, .pl, etc.)
	Don't fall into RPC with your URIs
	Do limit your URI space as much as possible
	Do keep path segments short
	Do prefer either /resource or /resource/; create 301 redirects from the one you don't use
	Do use query parameters for sub-selection of a resource; i.e. pagination, search queries

	https://fosspost.org/things-to-do-after-installing-fedora-34/
	https://www.debugpoint.com/2021/04/10-things-to-do-fedora-34-after-install/