kristofleroux

How to install CUDA / cuDNN / TensorRT on Ubuntu

sudo apt update && sudo apt upgrade

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

Extensions I use or want to use in VS Code.

I add links and explanations so you can use them too if you want.

Such as syntax highlighting and linting.

	# OpenClaw Implementation Prompts

	Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter.

	---

	## 1) Personal CRM Intelligence

	```
	Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach.

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	# To run command: mesop main.py

	import mesop as me
	import google.generativeai as genai
	import json
	import typing_extensions

	@me.stateclass
	class Article:
	title: str

	# Docker compose to set up containers for all services you need:
	# VPN
	# Sonarr, Radarr, Lidarr, Qbittorrent
	# Non-VPN
	# Plex, get_iplayer
	# Before running docker-compose, you should pre-create all of the following folders.
	# Folders for Docker State:
	# /volume1/dockerdata. - root where this docker-compose.yml should live
	# /volume1/dockerdata/plex - Plex config and DB
	# /volume1/dockerdata/sonarr - Sonarr config and DB

	from bs4 import BeautifulSoup
	import requests
	import datetime
	import logging
	import csv

	def setLogger():
	logging.basicConfig(level=logging.INFO,
	format='%(asctime)s - %(levelname)s - %(message)s',
	filename='logs_file',

	http://www.electricmonk.nl/log/2008/08/07/dependency-resolving-algorithm/

	Here's a little explanation of a possible dependency resolution algorithm. I've made this as basic as possible, so it's easy to understand. If you're at home in (graph) algorithms, this post is probably not of much interest to you.

	Premise

	Suppose we have five objects which all depend on some of the other objects. The objects could be anything, but in this case let's say they're very simple software packages (no minimal versions, etc) that depend on other packages which must be installed first. How does one find the right order of installing the packages?


	Take, for instance, the following scenario: Software package 'a' depends on 'b' and 'd'. 'b' depends on 'c' and 'e'. 'c' depends on 'd' and 'e'. 'd' depends on nothing, nor does 'e'. When we visualize this, we get something like this: