Deep Learning
In this post, we will learn what Batch Normalization is, why it is needed, how it works, and how to implement it using Keras. Batch Normalization was first introduced by
This summer I am doing an internship at Big Vision LLC under the guidance of Dr. Satya Mallick. In this post, I will describe the problem I was asked to
Billionaire investor and entrepreneur Peter Thiel’s favorite contrarian questions is What important truth do very few people agree with you on? If you had asked this question to Prof. Geoffrey
In this article, we will learn deep learning based OCR and how to recognize text in images using an open-source tool called Tesseract and OpenCV. The method of extracting text
We learn how to use the openpose model with OpenCV DNN Module
In this post, we share some formulas for calculating the sizes of tensors (images) and the number of parameters in a layer in a Convolutional Neural Network (CNN). This post
In this article, we will learn about autoencoders in deep learning. We will show a practical implementation of using a Denoising Autoencoder on the MNIST handwritten digits dataset as an
The first batch of our course on Computer Vision for Faces has graduated and I am very excited to announce the Best Project Award for our course. It has a
This post is part of the series on Deep Learning for Beginners, which consists of the following tutorials : In this post, we will learn about different activation functions in
In this post, we will introduce several new concepts associated with the general problem of classification involving more than two classes. This is sometimes referred to as multinomial regression or
In this article, we will learn about feedforward Neural Networks, also known as Deep feedforward Networks or Multi-layer Perceptrons. They form the basis of many important Neural Networks being used
1. Deep Learning Frameworks Deep Learning is a branch of AI which uses Neural Networks for Machine Learning. In the recent years, it has shown dramatic improvements over traditional machine
