Backpropagation Implementation and Gradient Checking Approximate implementation of backpropagation without regularization using NumPy, and Gradient Checking for the Derivatives. machine-learning andrew-ng

Backpropagation Derivation The post delves into the mathematics of how backpropagation is defined. It has its roots in partial derivatives and is easily understandable andrew-ng machine-learning mathematics

Program in PyTorch PyTorch is an open source machine learning library for Python, based upon Torch, an open-source machine learning library, a scientific computing framework, and a script language based on Lua programming language. machine-learning pytorch library

Images, Noise and Filters Though images are generally associated with vision and perception, it can also be understood as a function in the field of computer science. machine-learning computer-vision image-processing udacity

What is Computer Vision? The goal of computer vision is to write computer programs that can interpret images. machine-learning computer-vision image-processing udacity

Understanding TensorFlow TensorFlow is an open source, data flow graph based, numerical computation library. Nodes in the graph represent mathematical operations, while edges represent the multidimensional data arrays communicated between them. machine-learning tensorflow library

Neural Networks: Cost Function and Backpropagation Intuition behind the idea of backpropagation and its extension to calculate cost function machine-learning andrew-ng

Neural Networks Intuition The relationship between logistic regression and neural networks. Explaination about how neural network is the logical successor of logistic regression machine-learning andrew-ng

Neural Networks Theory An Artificial Neural Network is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information machine-learning andrew-ng