All to understand and practice A.I. in a simple way
We will see in this article, how with the YOLO neural network we can very simply detect several objects in a photo. The objective is not to go into the details of the implementation of this neural network (much more complex than a simple sequential CNN) but rather to show how to use the implementation which was carried out in C ++ and which is called Darknet.
In this article we will discuss the concept of Transfer Learning … or how to avoid redoing long and consuming learning by partially reusing a pre-trained neural network. To do this we will use a network which is the reference in the matter: VGG-Net (vgg16).
I propose in this article to create a convolutional neural network to do NLP, and for the data I will use a dataset that you can simply find in the Kaggle datasets: FrenchFakeNewsDetector. You have understood the objective is twofold: on the one hand to see how we can use the convolution technique with vectors (1 dimension instead of images with 2+ dimensions) and on the other hand to do NLP with data in French.
In this article we will see step by step how to create and use a convolutional neural network (CNN) to classify images.
In this article, I suggest you discover a brilliant tool that allows you to better understand how a neural network works and the real impact of its main settings.
Discover Auto-ML with AutoGluon. Simple accelerator or real revolution in the way of creating machine learning models? get an idea by doing …
In this article we will see by practice if deep learning via keras can help us find Titanic survivors more efficiently than traditional algorithms.
by 
