Ridge regression, LASSO, Elastic Net

I. Introduction In previous posts, we discovered some popular convolutional neural networks (CNNs) such as LeNet, AlexNet, VGG, NiN, GoogLeNet at which the model performance increases proportionally with the number of layers. One may ask if models can learn better with a higher number of layers? Generally, it is not always correct…

1. Introduction GoogLeNet is a deep convolutional neural network that was proposed by Szegedy et al. [1]. This network won the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC-2014) where 92.3% classification performance was achieved. …

This post aims to introduce briefly two classic convolutional neural networks, VGG16 and NiN (a.k.a Network in Network). We are going to discover their architectures as well as their implementations on the Keras platform. …

Alexnet is a convolutional neural network that was designed by Alex Krizhevsky, in collaboration with Ilya Sutskever and Geoffrey Hinton. In ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2010, this network was trained to classify 1.2 million high-resolution images into 1000 different classes. It achieved top-1 and top-5 error rates…

LeNet (or LeNet-5) is a convolutional neural network structure proposed by Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner in 1989. The first purpose of this network is to recognize handwritten digits in images. …

Activation functions are mathematical functions that are attached to each neuron in the networks and determine whether it should be activated or not. Typically, in each layer, the neurons perform a linear transformation on the input using the weight and bias: Then, an activation function is applied to the above…

Convolutional neural network (CNN) is a class of deep neural network and is commonly applied for processing structured arrays of data such as images. CNN is widely used in computer vision. They have many applications in image and video recognition, image classification, natural language processing, etc. A convolutional neural network…

Machine learning engineers do not only need to have good programming skill, but they also need to have some skills of a data scientist as collecting and managing data, skills of statistician for analyzing data, and also skills of a mathematician …. It is because a machine learning project requires…

As you know, the applications of Machine learning appear everywhere in our life. For example, when you search for something in Google, based on Machine learning algorithms, it recommends to you the most performance results related to your keywords. Facebook, Youtube, Amazon also use recommendation systems for suggesting the users…