A deep dive into the mathematical and technical aspects of legacy, material possession, and social impact. Why what we often strive for may not last as long as we think.
A personal perspective on the rapid evolution and implications of AI and ML technologies.
Arbitrary code execution during compliation
Rusty the bucket a performance benchmark for building pandas
A brief introduction to ownership in Rust
Why merkle trees are becoming a everyday data structure that most engineers should know
A description of how to setup a project using yarn with typescript support from the beginning
A short but concise description of what side effects mean in software development
A tutorial on how to setup the correct credentials and service account for creation of sheets
Predicting a recession using simple metrics
Music Genre Classification using fastai and deploy on GCP
Going broad in a graph: Introduction to Breadth First Search
Tricks for string manipulation handling
Simple tricks to go from nothing to prototype of app
Data structures and algorithms - 2sum
Short introduction to why to learn algorithms
EchoServer send whatever you `$ curl localhost:4000` 'sent to it'. "sent to it"
How to calculate the Probability of an event occuring by also using the Z-score
Gradient descent is one of 'greatest hits' algorithms. This posts gives a detailed explained and walkthrough of why and how it is implemented and applied to an example for linear regression
Any text-based entity or text-based column for upstarts or demos can be populated by generating mock data from a already learnt distribution or a encoding/decoding using textgen.
A neural network to play frappy bird with a genetic algorithm with different speeds and watch the progress.