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cs-notes
Programming
Web
(crossover) The Networking in Web Development
Typescript
React
React 1 — Virtual DOM and Events
React 2 — Components
CSS Positioning
JavaScript Shenanigans
RWD (Responsive Web Design)
C & C++
Bit-fields
Everything Numbers
Function Pointers and its Confusing Notations
Getting Zero Befuddlement from Pointer Declarations
Handling Multiple Files
Operator Precedence
Pointers — The Stupid and The Informative
Reason Behind int main(void)
Swapping Two Ints (Not recommended) Without a Temporary Variable with Bitwise XOR
The Two Alllocs in stdlib.h
Useful Functions that are Abused in C
Variable Length Argument Lists
What char Stores (ASCII Table)
define vs const declaration in global scope
goto
printf and scanf notation
static
structs
weird boolean expressions that work
Python
*args and **kwargs
A Python Program Intended as a Script
Checking for types & is
Function Decorators
Lambda functions (lambda)
Project Management with uv
Python Builtins
Python Function Argument Pass Method
Special Class Methods (besides from __init__)
The Walrus Operator
deleting stuff
sets
yield
General Programming & Comp Sci
Arrays vs Pointers
Bitwise Operators
Cycle
Divide and Conquer (feat. Merge Sort)
Dynamic Programming
Faster Everything with Bitwise Operations
Greedy
OOP Things
Object Files, Shared Libraries, and some others about Compilation
Passing Variables Declared within Function as Return Variables
RNG
Topological Sort
Wiser Control FLow
assert
asyncio
unions
AI
Real World
Opencode with Custom (Local) Models
Prompt Engineering Framework
llama.cpp compilation with CUDA (linux)
vllm on Linux
Architectural and Conceptual
Activation Functions
Explanation of LLMs Being Few-shot Learners + How Tools are Provided to LLMs
Loss Functions
ML (Backpropogation)
MLPs (Feed-Forward Networks)
Mixture of Experts - A Brief
Neurons
RNNs, CNNs, Bag of Words, Bigrams and More
Scalars, Vectors, Matrices, and Tensors; How Tensors and other Data Types > 1D Get Used in MLP
Transformers and Modern LLMs
Misc
Git
Linux, Unix, and OS
The Stack and the Heap
cron and crontab
cut
find
sed
tar and gzip
Security and Cryptography
EDCSA
HTTPS
JWTs (JSON Web Tokens)
OAuth2
Public Key Cryptography
RSA
TLS (Transport Layer Security)
Networking
Commands
arp
host (& other host lookup tools)
ifconfig or ip a (checking networking configuration)
lsof
netcat
netstat
ping
route
tcpdump and Wireshark
traceroute
whois
Conceptual
Broadcast domain vs Subnets
DNS and the Hosts File
Ethernet
HTTP
Hubs, Switches, and Routers
IP
MAC Addresses, ARP, & ND
Network Traffic Blockers and Manglers
Proxy Server
Sockets
TCP - IP, UDP, ICMP, Ports
The Four Layers
Home
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cs-notes On Github
AI
Architectural and Conceptual
Explanation of LLMs Being Few-shot Learners + How Tools are Provided to LLMs
Explanation of LLMs Being Few-shot Learners + How Tools are Provided to LLMs
LLMs are few-short learners
paper
#ai #ai/conceptual #ai/ml