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Integrating neural networks with relational learning to reach beyond the current state of structured deep learning models, such as GNNs.

What is Confusion Matrix and Advanced Classification Metrics?

Cheatsheet for precision & recall

Precision and recall - Wikipedia

A model of an artificial neuron is reviewed here. We know that any complex neural network is mostly composed of such artificial neurons. Here, we define a Python class for the neuron, and then use it in an example. The whole Python code is also available at the mentioned GitHub page.

Sigmoid functions ae mainly used for neural networks and deep learning as activation functions.

This article presents the equations that we use when performing weight-update computations, and we’ll also discuss the concept of backpropagation.

Sometimes, you see a diagram and it gives you an ‘aha ha’ moment Here is one representing forward propagation and back propagation in a neural network I saw it on Frederick kratzert’s blog A brief explanation is: Using the input variables x and y, The forwardpass (left half of the figure) calculates output z… Read More »An elegant way to represent forward propagation and back propagation in a neural network

Are you struggling to get your start in machine learning using Python? In this step-by-step, hands-on tutorial you will learn how to perform machine learning using Python. Let's get started!

This blog post will be introduction to understanding Exponential Linear Unit (ELUs) activation function in Deep Learning. Best way to learn…

A model of an artificial neuron is reviewed here. We know that any complex neural network is mostly composed of such artificial neurons. Here, we define a Python class for the neuron, and then use it in an example. The whole Python code is also available at the mentioned GitHub page.

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