Let us talk about one underrated concept of distributed computing. I came across MapReduce—a programming model for processing large datasets across many machines—and this post covers where it came from, where it is used, and a full example you can run locally or scale out.
I feel very empty writing this, not because I didn't achieve what I set out this year, but more so because life took a 180° turn, I found myself juggling the Nigerian imposed service year and my full time remote job.
Many libraries and tools perform various tasks in processing files, images, and documents. PDF files are a good example of files that can undergo several processing stages using Python libraries and AI models. Reducing the size of a PDF file can be necessary for various reasons, and various tools can accomplish this. One fascinating way is to use the PyMuPDF library.
In a world where LLMs have evolved beyond the ability to perform smart interactions and respond to prompts, AI agents have provided a great platform for models to carry out various tasks that require high reasoning, while also adapting to a task without any need for human intervention.
If you have limited RAM to run the local version of Deepseek, you can make use of their extremely cheap API and use it as your default model in Cursor.
Year in Review, wins, losses and lessons. This year was a lot; I experienced my lowest and highest points in just 365 days. Never the less, it turned out to be my most productive year by miles.
Design engineering bridges design and engineering in web development, focusing on creating visually appealing, performant, and user-centered products. This article explores how combining systematic thinking, reusable components, and UX attention delivers cohesive, polished, and responsive experiences. We'll dive into principles, workflows, and tools for creating high-quality products at scale with seamless collaboration.
A few days ago Meta released a new version of their open source Large Language Model (LLM) called the Llama 3.1 in three variants, the 8B, 70B, and 405B which represents the size of tokens, with the smallest being 8Billion tokens.
Welcome back to the ML Series, In the previous article in this series we implemented a Multiplayer Perceptron Model, that was an introduction into Neural Networks using a very basic architecture. Today we are going to be implementing a Convolutional Neural Network (CNN) using pyTorch and testing using the MNIST handwriting dataset.
Neural networks are algorithms created explicitly to simulate biological neural networks. The idea behind the Neural networks was to created an artificial system that would function like the human brain. At the basic level a Multi Layer Perceptron (MLP) is the simplest form of a Neural Network.
As a prerequisite for attaining my Bachelor's degree in Computer Engineering, I enrolled in a course titled Microcomputer Hardware and Software. An integral component of this course was the development of a project utilizing a microcontroller.
It is currently 3 a.m. (WAT), and the silence is deafening, quite apart from the constant cricket sound. Waking up before the crack of dawn has been a habit I have had for a while, but I took it up a notch by setting my alarm for 3 a.m., a decision that has made me way more productive than I used to be.
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