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Photo by Yancy Min on Unsplash

Git has a feature that “can make your git experience simpler, easier, and more familiar: aliases.

If you use git regularly this feature can really make a difference especially if you repeat a lot of git commands. Basically, you can create aliases (shortcuts) for everything that you might think! For example, instead of having to type “git commit — amend” you can create an alias and only type “git ca”! …


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Photo by Pietro Jeng on Unsplash

This post aims to summarize the most important aspects of Pedro Domingo’s article: “A few useful things to know about machine learning”.

The goal of the main article is to “communicate the folk knowledge” about machine learning that usually does not come in the scientific articles. Pedro has a lot of experience in ML so I think that these tips, based on his experience, are quite relevant! You can find the article here — https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf.

Also, if you like the work that my fellow compatriot does (I’m also Portuguese :)), I recommend his book about machine learning — The Master…


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Photo by Yancy Min on Unsplash

Hi, I’m a recent Master graduate and despite having 2 years of work experience I only started doing serious code review for the last 7 months in my new job.

Being a Junior Software Developer I always struggled with code reviews because I was “afraid” of the Senior Developers. We never learn how to do a code review in school, so I searched on the internet to find guides and tips for a good review. I found many websites but none of them had a clear and simple checklist.


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Photo by Charles Deluvio on Unsplash

“What machine learning algorithm should I use? “ or “How to choose a machine learning algorithm?” Let’s start with: there is no straightforward answer! 😤 😕 however, there are some factors that clearly influence the choice of an algorithm.

One of the key decisions that typically a data scientist has to make is the choice of an algorithm that will use the data to hopefully predict correctly the expected outcome. However, faced with a lot of algorithms, data scientists find themselves overwhelmed. Despite the fact that there are no direct and straightforward answers to the question “Which algorithm will I…


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Photo by Hunter Harritt on Unsplash

In Machine Learning (ML), there are many terms and concepts and many of them may not be used consistently. When you start studying Artificial Intelligence you will come across with so many concepts. In this article, I will try to explain some of those concepts in a simple way.

If you’re like me, you like simple and direct explanations. With that in mind, I will explain the two types of parameters in ML, and then give a clear explanation of the different hyperparameters.

There are two types of parameters: model parameters and hyperparameters.

Model parameters are the parameters that the…

Filipe Good

Big Data Engineer & AI Master’s Degree Student

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