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Photo by Christin Hume on UnsplashAn overview of approaches, evaluation metrics, and best practicesIntroductionThese days I am working to develop a Machine Learning algorithm that is able to identify different types of damage found in buildings. The damages are not all the same, they each have different causes and risks, so we have identified about 4 different types of fractures. The algorithm will then be deployed on a drone that automatically is going to take pictures of the building and will be able to tell what and…

Wild Marcello in Africa (Image By Author)Learn about Yolov4 and Darknet to train a Custom Object DetectorIntroductionI recently started working in the field of computer vision. And in these early days, I’m studying how the various algorithms of object detection work. Among the most well-known ones are R-CNN, Fast R-CNN, Faster R-CNN and of course YOLO.In this article, I want to focus on the last mentioned algorithm. YOLO is the state of the art in object detection and there are endless use cases where YOLO can be used.…

Dive into performance evaluation metrics and heatmap visualization of confusion matrix using PythonPhoto by The Jopwell Collection on UnsplashIn this new article of this “Ace your Machine Learning Interview” series, I begin to address a different topic. Instead of describing a new Machine Learning algorithm, I will show you how to evaluate whether an algorithm is working well. Knowing how to evaluate an ML system well is as important as developing the system itself.I hope that you will find it useful as you tackle your…

Photo by Fotis Fotopoulos on UnsplashLearn how to debug your Python program with Visual Studio CodeIntroductionI once read that in programming an error in code is called bug for a very specific reason. When computers were still huge mainframes (a long, long time ago) it happened that a bug got stuck in the gears and that’s why the program wouldn’t run anymore!Today by bugs we mean a very different thing. Everyone, even the most experienced and paid programmers in the world write code that contains bugs, but the skill lies…

Photo by CoWomen on UnsplashDive into Ensemble Learning with AdaBoost from scratch using PythonIn this article of my series “Ace your Machine Learning Interview” I continue to talk about Ensemble Learning and in particular, I will focus on Boosting algorithms with special reference to AdaBoost. I hope that this series in which I review the basics of Machine Learning will be useful to you in facing your next interview!😁In case you are interested in the previous articles in this series, I leave the links here:Ace your…

Photo by airfocus on UnsplashDive into Ensemble Learning with Hard Voting Classifiers using PythonWe have come to the seventh article dedicated to my “Ace your Machine Learning Interview” series in which I recap some of the basics of Machine Learning hoping that it will be helpful to you in facing your next interview!😁In case you are interested in the previous articles in this series, I leave the links here:Ace your Machine Learning Interview — Part 1: Dive into Linear, Lasso and Ridge Regression and their assumptionsAce…

Photo by Dylan Gillis on UnsplashDive into Decision Trees using PythonToday I keep going with the sixth article of my “Ace your Machine Learning Interview” series by talking about Decision Trees!In case you are interested in the previous articles in this series, I leave the links here:Ace your Machine Learning Interview — Part 1: Dive into Linear, Lasso and Ridge Regression and their assumptionsAce your Machine Learning Interview — Part 2: Dive into Logistic Regression for classification problems using PythonAce your…

Photo by Austin Distel on UnsplashDive into Kernel Support Vector Machines using PythonAs I mentioned in the previous article in this series, I will now go on to talk about Support Vector Machines, and how they can be used to classify nonlinearly separable datasets using the kernel trick.If you missed the previous articles in this Ace your Machine Learning Interview series, I leave the links below:Ace your Machine Learning Interview — Part 1: Dive into Linear, Lasso and Ridge Regression and their assumptionsAce your…

Photo by Headway on UnsplashDive into Support Vector Machines using PythonThis is my fourth article dedicated to the series I started about Machine Learning fundamentals to know in order to approach your interview. I leave you the links here to the previous articles.Ace your Machine Learning Interview — Part 1: Dive into Linear, Lasso and Ridge Regression and their assumptionsAce your Machine Learning Interview — Part 2: Dive into Logistic Regression for classification problems using PythonAce your Machine Learning…

Photo by Kenny Eliason on UnsplashDive into Naive Bayes Classifier using PythonThis is the third article in this series I have called “ Ace your Machine Learning Interview” in which I go over the foundations of Machine Learning. If you missed the first two articles you can find them here :IntroductionNaive Bayes is a Machine Learning algorithm used to solve classification problems, and it is so-called because it is based on Bayes’ theorem.An algorithm referred to as a classifier, assigns a class to each instance of data.…