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Photo by Quino Al on Unsplash

Nothing compares to math and programming when it comes to backwards teaching. Nobody comes out of schooling thinking either of these is a particularly creative discipline. Yet real-world math and programming only look like their scholastic counterparts on the surface.

Languages only use rules insomuch as they liberate the speaker to bring about something new. The mindless symbol-shuffling promulgated by today’s teachers is as impaired as their ability to create.

Language is about expression. If you aren’t *creating* something then you aren’t speaking the language. People don’t communicate through thoughtless adherence to rules. …


End-to-End Steps for Turning Your Idea into Something Real

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Photo by Hello I’m Nik 🎞 on Unsplash

When Form Follows Function

People have ideas. Lots of ideas. But how often do they turn those ideas into something real? There is a distinct difference between what’s in our heads and what can be created.

Most people don’t build software. This includes many people on actual software teams. If you’re not coding now you see the creation of working software as someone else’s job. Perhaps you’ve wanted to start learning (or relearning) yourself but assume it takes too long, is too technically challenging or just not something that interests you.

Ideas typically live as drawings, post-its, mockups and “clickable apps”, all of which…


Embracing the “Correlation of the 21st Century.”

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The logical relations between various concepts underlying Mutual Information.

Dependency

Causality is a central concept in our lives. It refers to the idea that one event influences another event. Our perception of causality underlies many of our personal opinions. If I believe the internet makes people dumber, or that the President has made things worse, I am suggesting a causal connection; real or not.

In business we look to understand what makes a good hire, a good decision, a good product. In government we create new legislation and policies based on evidence for social and economic causes. …


Facilitating Scientific Discovery by Uncovering Analogical Connections

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INTRO

In a recent Nature article¹, researchers used word embeddings to discover candidate compounds for materials science. One of the authors, Vahe Tshitoyan, also published an overview² of the work on Medium. Specifically, they showed that new thermoelectric materials could be discovered by mining scientific journals.

I think this is an interesting use of the well-known word embeddings technique. With word embeddings, we look to create vector representations for important words in a document. Once vectorized, these words can be used with the usual vector operations from linear algebra. Thus we can add and subtract words to find results that match…


Detecting, Extracting and Classifying Circuit Board Defects using Image Processing and Deep Learning

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The Printed Circuit Board (PCB) is in most electronic products, mechanically supporting and connecting components along conductive tracks. Their prevalence underlies the modern electronics industry, with a world market exceeding $60 billion¹.

PCBs are prone to a variety of defects that impede proper manufacturing, costing companies money. Defects such as shorts, spurs, mousebites, and pinholes cause issues like current leakage and open circuits, quickly degrading performance or rendering PCBs useless. PCB manufacturers must strive to ship defect-free units to remain competitive and ensure customer satisfaction.

Failure analysts are employed to ensure defects are kept to a minimum. But inspecting and…


The Fluid Universality of Math and Computation

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Most people are uncomfortable with the notion that human cognition is nothing more than computation. After all, humans are currently far superior to machines at most tasks. It seems too limiting to frame the abilities of the human mind in terms of some symbol-churning machine that dryly converts inputs into outputs.

But the arguments around why this is seem to always fall flat. What is it about human thinking that is so different? If human intelligence is something more than computation where does this more come from?

I argue that people’s aversion to the machine analogy stems from their misunderstanding…


Some Thoughts for Tomorrow’s Generation

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You cannot engineer your career. You cannot craft your success. Your accomplishments will not come by following a plan, mimicking your hero’s habits, or staying up-to-date on the latest trends.

Your luminaries are statistical aberrations, with stories no more interesting or unique than those who have failed. You are reading but one of countless plausible narratives in an ocean of silent evidence.

That feeling you get after purchasing the latest book from the business section is just the recycled high that accompanies the illusion convenient narratives provide. An endless attempt at grasping the mirage of an unworkable blueprint.

You are…


A Conceptual Tour of Why Intelligence Testing Fails in Both Scientific Validity and Real-World Utility

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The debate over the validity of IQ is nothing new. Every once in a while a fresh report pops up against the background of ongoing intelligence research, either defending or attacking its foundations. Proponents of IQ argue the research behind the intelligence quotient is sound and its utility proven. Opponents argue IQ studies have never rested on good science, exaggerates claims, and has done far more damage than good.

Recently this debate has arrived on social media by way of Twitter. 2 major voices in this debate are Nassim Nicholas Taleb (author of Incerto) and Claire Lehmann (founding editor of…


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What is D3 Observable?

I’ve written previously about bringing D3 into web applications here, looking at how to bind D3 visuals to UI elements. The purpose was to encourage moving beyond stand-alone visuals and get people prototyping fuller applications. Real applications solicit feedback because they get used, helping us validate analyses beyond usual statistical measures. IMO if you’re not building a real product you’re not really learning/doing data science.

The previous article still stands, but D3 is changing directions towards what it calls Observable (formally known as d3.express). Observable provides a playground of sorts, allowing users to modify D3 code online inside a notebook


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R and Python are the bread and butter of today’s machine learning languages. R provides powerful statistics and quick visualizations, while Python offers an intuitive syntax, abundant support, and is the choice interface to today’s major AI frameworks.

In this article we’ll look at the steps involved in creating libraries in R and Python. This is a skill every machine learning practitioner should have in their toolbox. Libraries help us organize our code and share it with others, offering packaged functionality to the data community.

NOTE: In this article I use the terms “library” and “package” interchangeably. While some people…

Sean McClure

Founder Kedion, Ph.D. Computational Chem, builds AI software, studies complexity, host of NonTrivial podcast.

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