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  • Backpropagation from Scratch

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    Artificial Intelligence (AI) is a very hot buzzword these days. Many people are excited (or scared 😱, depending on how you view AI) about its capabilities! Machine learning is the engine that powers any AI system. We can classify supervised machine learning algorithms into two categories. First one is traditional algorithms which are not based…

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  • Perceptron Algorithm: The Grand-daddy of AI

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    Perceptron: The Genesis In the summer of 1958 a 30-year old research psychologist Frank Rosenblatt invented a machine that can be fed with some punch cards and the machine was capable of telling which cards were marked on the right and which cards were marked on the right [1]. The name of the machine was…

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  • Fit, Underfit, and Overfit in Machine Learning

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    Today I am going to cover an important aspect of any machine learning model. When we build a machine learning model we always want the model to be fit, we do not want overfitting or underfitting. I’ll present a very simple example to show the implications of overfitting and underfitting. Let’s take a very simple…

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  • Interpretation of Logistic Regression Coefficient

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    How to Interpret a Logistic Regression Model Coefficient To interpret a logistic regression coefficient you only need three key things to understand. 1. Logistic function, 2. Logit function, and 3. Odds. If you understand these three concepts then you should be able to interpret any logistic regression model! In this article I’ll cover all these…

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