Vinoth Pandian vinothpandian

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

Nginx Reverse Proxy for homelab services using SSO

NOTE: This document has now been added to the nginx-sso wiki, here. Any further updates will be made there.

Using:

Docker
Nginx
nginx-sso

A complete list of books, articles, blog posts, videos and neat pages that support Data Fundamentals (H), organised by Unit.

Formatting

If the resource is available online (legally) I have included a link to it. Each entry has symbols following it.

⨕⨕⨕ indicates difficulty/depth, from ⨕ (easy to pick up intro, no background required) through ⨕⨕⨕⨕⨕ (graduate level textbook, maths heavy, expect equations)
⭐ indicates a particularly recommended resource; 🌟 is a very strongly recommended resource and you should look at it.

Testing

Helpers and examples for unit testing on Angular applications and libraries.

Deploying a subfolder to GitHub Pages

Sometimes you want to have a subdirectory on the master branch be the root directory of a repository’s gh-pages branch. This is useful for things like sites developed with Yeoman, or if you have a Jekyll site contained in the master branch alongside the rest of your code.

For the sake of this example, let’s pretend the subfolder containing your site is named dist.

Step 1

Remove the dist directory from the project’s .gitignore file (it’s ignored by default by Yeoman).

PyCon 2012 Digest

from DevOps team {rduplain,mattd,teebes}, to mobile developers at WillowTree Apps

	{
	"parser": "@typescript-eslint/parser",
	"parserOptions": {
	"project": "./tsconfig.json",
	"tsconfigRootDir": "."
	},
	"env": {
	"browser": true,
	"jest/globals": true
	},

	import numpy as np
	from keras import backend as K
	from keras.models import Sequential
	from keras.layers.core import Dense, Dropout, Activation, Flatten
	from keras.layers.convolutional import Convolution2D, MaxPooling2D
	from keras.preprocessing.image import ImageDataGenerator
	from sklearn.metrics import classification_report, confusion_matrix

	#Start
	train_data_path = 'F://data//Train'

	import pandas as pd

	class ChainedAssignent:

	""" Context manager to temporarily set pandas chained assignment warning. Usage:

	with ChainedAssignment():
	blah

	with ChainedAssignment('error'):