Data augmentation in data analysis are techniques used to increase the amount of data by adding slightly modified copies of already existing data or newly created synthetic data from existing data. It acts as a regularizer and helps reduce overfitting when training a machine learning model. …

Regularization is a technique used in an attempt to solve the overfitting problem in statistical models.

First of all, I want to clarify how this problem of overfitting arises.

When someone wants to model a problem, let’s say trying to predict the wage of someone based on his age, he…

Error, Loss Function, Optimization

The basic principle used by a number of machine and deep learning algorithms is called supervised learning. You can think of it as learning from mistakes, since it uses iterative procedure to find a minimum of PREDICTION ERROR of a machine learning model for the given training data. The error…


Recursion is a process that refers to the very object of the process at a point in the process. In other words, it is an approach whose description leads to the repetition of the same rule.


Take a look at the following algorithm that calculates a number x taken to…

Hamdi Ghorbel

student at holbertonschool

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