First unveiled on amitnikhade.com They also have a weak spot — they can be hacked! Adversarial attacks, where inputs are tweaked to mislead these networks, have become a concern. In this post, we’ll explore the basics of hacking neural networks in a responsible and ethical manner. What is it? The FGSM (Fast Gradient…

Originally published on amitnikhade.com “The Markov chain captures the essence of independence between the past and the future, highlighting that the present state holds the key to predicting what lies ahead.” The Markov property says that the future is only influenced by the present, not the past. A Markov chain…

A powerful machine learning technique that merges neural networks and Bayesian statistics to make predictions that are both accurate and reliable. Originally published on amitnikhade.com Imagine you want to predict whether your friend will come to your party. …

Get ready to be transported to a whole new dimension with quantum teleportation — where the impossible becomes possible! Originally published on amitnikhade.com What exactly is quantum teleportation? Quantum teleportation is an amazing idea in quantum mechanics that allows us to send information from one place to another without any physical connection between them. It’s…

The model has been trained and dumped, what next? Originally published on amitnikhade.com Deploying a deep learning model in production is a complex task that requires careful attention to both technical and practical details. …

The smooth and non-monotonic function that can be used in place of the commonly used ReLU activation function. Originally published on amitnikhade.com Introduction to Activation Functions In machine learning and deep learning, an activation function is a mathematical function that is applied to the output of a neural network layer to introduce non-linearity into the network, allowing it…

An Attention Mechanism for Channel-Wise Feature Enhancement originally published on amitnikhade.com Introduction Squeeze-and-Excitation (SE) Networks are a type of artificial neural network that helps computers better understand and recognize images. They do this by focusing on the important parts of an image and ignoring the unimportant parts. The SE module in…

Unlocking the mysteries of quantum computing with the power of gates. (originally published on amitnikhade.com) Introduction A quantum gate is a basic building block of quantum computation, which performs a specific unitary operation on a quantum state. …

Precision at a fraction of the size: Experience the power of quantization for your deep learning models Originally published on amitnikhade.com Originally published on amitnikhade.com Introduction Model quantization is a technique for reducing the precision of the weights and activations of a neural network model. This process can be used to…