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First introduced by Rosenblatt in 1958, The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain is arguably the oldest and most simple of the ANN algorithms. Following this publication, Perceptron-based techniques were all the rage in…

Now that we have implemented neural networks in pure Python, let’s move on to the preferred implementation method — using a dedicated (highly optimized) neural network library such as Keras. Today, I will discuss how to implement feedforward, multi-layer networks…

Backpropagation is arguably the most important algorithm in neural network history — without (efficient) backpropagation, it would be impossible to train deep learning networks to the depths that we see today. Backpropagation can be considered the cornerstone of modern neural…

You might have started to notice a pattern in our Python code examples when training neural networks. There are four main ingredients you need to put together in your own neural network and deep learning algorithm: a dataset, a model/architecture,…

In this tutorial, we will discuss the concept of weight initialization, or more simply, how we initialize our weight matrices and bias vectors. This tutorial is not meant to be a comprehensive initialization technique; however, it does highlight popular methods,…

In this tutorial, you will learn: What gradient descent is How gradient descent enables us to train neural networks Variations of gradient descent, including Stochastic Gradient Descent (SGD) How SGD can be improved using momentum and Nesterov acceleration To learn…

In this tutorial, you will learn how to perform face recognition using Local Binary Patterns (LBPs), OpenCV, and the cv2.face.LBPHFaceRecognizer_create function. In our previous tutorial, we discussed the fundamentals of face recognition, including: The difference between face detection and face…

In this tutorial, you will learn about face recognition, including: How face recognition works How face recognition is different from face detection A history of face recognition algorithms State-of-the-art algorithms used for face recognition today Next week we will start…

In this tutorial, you will learn how to compute image histograms using OpenCV and the cv2.calcHist function. Histograms are prevalent in nearly every aspect of computer vision. We use grayscale histograms for thresholding. We use histograms for white balancing. We…