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Since the dawn of time, living beings have demonstrated their ability to adapt to their ever-changing environment and improve from generation to generation. This ability
Reinforcement learning is, along with supervised and unsupervised learning, one of the three major machine learning techniques. This family of algorithms has been creating a
Manifold Learning is a technique that simplifies the visualization and analysis of complex, high-dimensional data sets, by finding underlying low-dimensional structures. Find out all you
The Kernel is a Machine Learning classification method. Find out everything you need to know about it, and how to train to become a Data
The Jensen-Shannon divergence is used to measure the similarity between two probability distributions, particularly in the field of Machine Learning. Find out everything you need
When designing a deep neural network, several types of first-level architecture can be used. One of these is the dense neural network. So what is
Introduction If you are getting started on a Data Science project, this article will be of interest to you! Before starting a Machine Learning project,
In a previous article, we showed just how indispensable Machine Learning Engineers are to companies, to the extent that the number of job offers has
Horizontal scaling consists of adding additional machines to an infrastructure, to adapt to increased demand on an application or website. Find out all you need
As far as future prospects are concerned, many hopes are pinned on unsupervised learning to improve cyber security or the identification of various diseases. In
Neural Style Transfer (NST) is a set of models and methods for transferring the visual style of one image to another, using images or videos.
In Machine Learning, an important step in the processing of data is its graphical representation, so that it can be visualized and its behavior better
