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Mastering Hadoop, Part 3: Hadoop Ecosystem: Get essentially the most out of your cluster

As we've already seen with the essential components (Part 1, Part 2), the Hadoop ecosystem is continuously evolving and being optimized for brand new applications. Consequently, various tools and technologies have developed over time...

Nine Pico PIO Wats with Rust (Part 2)

That is Part 2 of an exploration into the unexpected quirks of programming the Raspberry Pi Pico PIO with Micropython. For those who missed Part 1, we uncovered 4 that challenge assumptions about...

Nine Rules for SIMD Acceleration of Your Rust Code (Part 1)

SIMD (Single Instruction, Multiple Data) operations have been a feature of Intel/AMD and ARM CPUs because the early 2000s. These operations enable you to, for instance, add an array of eight i32 to a different array of...

AI Agents from Zero to Hero – Part 1

Intro AI Agents are autonomous programs that perform tasks, make decisions, and communicate with others. Normally, they use a set of tools to assist complete tasks. In GenAI applications, these Agents process sequential reasoning and...

Data Scientist: From School to Work, Part I

Nowadays, data science projects don't end with the proof of concept; every project has the goal of getting used in production. It will be important, subsequently, to deliver high-quality code. I even have been...

Learnings from a Machine Learning Engineer — Part 5: The Training

On this fifth a part of my series, I'll outline the steps for making a Docker container for training your image classification model, evaluating performance, and preparing for deployment. AI/ML engineers would like to deal...

Roadmap to Becoming a Data Scientist, Part 4: Advanced Machine Learning

Introduction Data science is undoubtedly probably the most fascinating fields today. Following significant breakthroughs in machine learning a couple of decade ago, data science has surged in popularity throughout the tech community. Every year, we witness increasingly...

😲 Quantifying Surprise — A Data Scientist’s Intro To Information Theory — Part 1/4: Foundations

Through the telecommunication boom, Claude Shannon, in his seminal 1948 paper¹, posed a matter that may revolutionise technology:How can we quantify communication?Shannon’s findings remain fundamental to expressing information quantification, storage, and communication. These insights...

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