Artificial Neural Networks, or ANN, as they are sometimes called were among the very first Neural Network architectures. They are inspired by network of biological neurons in our brains. I find it very important to mention here that the Artificial Neural Networks are only inspired by the biological neurons and are not designed to model …
Building an Artificial Neural Network from Scratch using Keras Read More »
In this blog post I will be talking about and reviewing a book that I have recently gone through- “Deep Learning for Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery & More”. But first, before we get started with it, I would like to emphasise on the fact that it is really one …
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The choice of activation function is very important and can greatly influence the accuracy and training time of a model. Swish is one of the new activation functions which was first proposed in 2017 by using a combination of exhaustive and reinforcement learning-based search. The authors of the research paper first proposing the Swish Activation …
Swish as an Activation Function in Neural Network Read More »
ELU, also know as Exponential Linear Unit is an activation function which is somewhat similar to the ReLU with some differences. Similar to other non-saturating activation functions, ELU does not suffer from the problem of vanishing gradients and exploding gradients. And similar to Leaky-ReLU and PReLU, and unlike ReLU, ELU does not suffer from the …
ELU as an Activation Function in Neural Networks Read More »
Over the period of past few years the most asked question by far has been this, Which is the best book to study machine learning. And at this moment there are more books about Machine Learning than you may ever want to read. Choosing a right book is one of the most important parts when …
Sigmoid function also known as logistic function is one of the activation functions used in the neural network. An activation function is the one which decides the output of the neuron in a neural network based on the input. The activation function is applied to the weighted sum of all the inputs and the bias …
Sigmoid as an Activation Function in Neural Networks Read More »
Rectified Linear Unit, otherwise known as ReLU is an activation function used in neural networks. An activation function is the one which decides the output of the neuron in a neural network based on the input. The activation function is applied to the weighted sum of all the inputs and the bias term. It is …
ReLU as an Activation Function in Neural Networks Read More »