Posted in 2021
La normalisation par lots
- 11 December 2021
Dans cet article, je vais vous parler d’une technique efficace pour améliorer vos modèles de deep learning et les rendre plus puissants: la normalisation par lots ou en anglais batch normalization. Nous allons suivre la chronologie suivant les grands points qui sont:
Brief introduction to Convolutional Neural Networks
- 17 August 2021
If you are reading this post, it means you know about convolutional neural networks (CNN) or you have heard about it before. But why should you read what I am offering you here? Indeed, there is a lot of documentation, tutorials, articles, and videos on this subject — often with complex mathematical notions that are difficult to understand. I read a lot on CNNs to understand part of it. It is a small and vast domain at the same time; once you understand the basics, leveling up becomes relatively straightforward.
Principal Component Analysis
- 14 May 2021
The Principal Component Analysis (PCA) is a dimension reduction technique widely used. Given a dataset with \(n\) features, the aim is to have \(k\) feature with \(k\le n\) so as the features retain most of the variation present in all of the original variables.
Empirical Mode Decomposition
- 06 May 2021
Introduced by Hilbert–Huang, Empirical Mode Decomposition (EMD) is a data-driven method that used as a propelling tool for analyzing and decomposing non-stationary and non-linear data. EMD generates a finite and often small number of the frequency and amplitude modulated signals, intrinsic mode functions (IMF).
What to know about Logistic Regression ?
- 23 April 2021
When it comes to make machine learning (ML) classification task, there is Logistic Regression which make compromise between performance and results. Through this article, we’ll deep into the different steps to make a ML algorithm, how Logistic Regression work and of course an explanation of Gradient descent.