COVID-19 showed us how challenging a crisis could be. For the climate crisis, though, there is no vaccine.

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Photo by Klara Kulikova on Unsplash

It is frustrating when anything stronger than us takes away our rights. COVID-19 thought us a hard lesson when it forced us to stay in lockdown for weeks or months. I don’t believe anyone enjoyed it, even though we were in the comfort of our homes; we still had food, air to breathe, electricity, internet.

The coronavirus is still an open wound. It takes precious lives every day. Nonetheless, we are confident humankind will survive it. …


Five tips to sharpen your storytelling and demonstrate the best value of your data science experiments.

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Photo by Emanuela Meli on Unsplash

I know… Slides. Most data scientists hate building them. It is frustrating because you spend loads of time designing them and, often, the results are not as good as you expect. But don't be sad, I am here to help you make your slide-building funnier.

As you may have already noticed, slides are the most popular tool to exchange knowledge within companies (big or small ones). Without them, few people pay attention to what you have to say. Presentations are so popular because human-beings are visual learners. A 2014 study from MIT measured that our brain can process images in about 13 milliseconds. …


It's not easy to think like a businessman when you are a data scientist. Here goes some advice.

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Photo by Tom Leishman from Pexels

Data scientists are commonly trained to measure the value of a piece of research or a mathematical technique. We read and write papers, reports, theses, and evaluate if the presented method is sound and useful to solve a particular problem. Sometimes the technique is so intriguing and fascinating that we want to explore it just because…

Data scientists are curious!

Curiosity is beneficial, but (mostly) we are not in the science business, we are doing science for business.

In the academic world, we invest in research to expand knowledge in that area. We seek the benefit for the humankind. In the industry, we better serve the business. If you are uncomfortable aiding your employer to profit, you should either work in academia or seek another job — one where you believe your efforts will serve a greater cause. …


Although data science became popular with the advances in machine learning and AI, science is a much broader topic.

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Image via Wikimedia Commons and adapted under Creative Commons Attribution-Share Alike 2.0 Generic license.

In the past few years, machine learning, artificial intelligence, and ultimately data science rose as the buzzword of the industry.

Of course, there is a reason for this phenomenon. New algorithms and new hardware made complex prediction systems affordable for many companies. It's not hard to find a use case in the industry about how they overcame a massive problem using a thousand-layers convolutional neural network. And really, this is a good thing.

Who never wanted a crystal ball?

Nevertheless, machine learning and artificial intelligence have been topics of research in academia for decades. They are not new. Now, they are just more accessible. …


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Photo by Egor Kamelev from Pexels

Quando você usa uma palavra no seu texto, ela fica na sua memória recente e você quer usá-la outra vez, e depois mais uma vez… Pelo menos comigo, isso acontece. Acho difícil evitar tal erro, mas podemos detectá-lo automaticamente.

No meu artigo anterior, mostrei como fiz um contador de palavras para colorir textos de acordo com a frequência das palavras. A ferramenta está disponível gratuitamente em:

http://werbos.herokuapp.com/conta_palavras

Hoje, vou contar como estendi a ferramenta e usei a frequência das palavras para avaliar a originalidade do parágrafo. Olha como fica:

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Medida de originalidade dos parágrafos dos dois primeiros capítulos de Dom Casmurro, de Machado de Assis.

Pausa para um aviso: Da forma como estou (arbitrariamente) definindo originalidade de um…


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Photo by Matan Segev from Pexels

E se criássemos uma inteligência artificial para revisar e criticar nossos textos? Melhor que ensinar as máquinas a jogar Xadrez, não? Ao menos para quem escreve.

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Photo by Caleb Woods on Unsplash

Como engenheiro e cientista de dados, sempre quis destrinchar meus textos com as mesmas ferramentas que uso para analisar dados. Porém, nunca dediquei tempo para fazer isso.

Gosto do meu editor de texto (o Scrivener). Ele guarda algumas estatísticas do projeto e até faz categorizações gramaticais com a ferramenta de foco linguístico. Porém, sinto falta de algumas de análises mais sofisticadas do texto. Por isso, decidi fazer meu próprio ajudante de escrita, um sidekick para o meu editor de texto predileto. …

About

Jonas Dias

Head of data science @ Evergen and aspiring writer, living in Australia. Passionate about innovation and creativity.

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