
Hyperparameter Tuning in Deep Neural Networks
One way to make your deep learning model more accurate and generate better results is to tune your model’s hyperparameters. By doing so, you can speed up your training process and optimize the outputs provided by the model. In this post, we try to figure out some ways to make...

Optimization Algorithms in Deep Learning
Building deep neural networks is one thing, but optimizing it to train faster with better accuracy is a completely different set of domain. So, it is very important that we focus on optimizing our algorithms to converge faster with desirable accuracy and details. In this post, we discuss about a...

Practical Aspects of Deep Learning  2
Welcome to the second part of “Practical Aspects of Deep Learning”. If you haven’t already gone through the first part, then you can read the post here. In this post, we will be discussing on how to prevent the model from diverging from a good solution and also efficient processes...

Practical Aspects of Deep Learning  1
Deep Learning is a subset of Machine Learning which has come to evolve highly in the past few years. It involves neural networks with the number of hidden layers greater than one, hence the term “deep”. The basis of a neural network in deep learning is Logistic Regression and one...

Implementation of a Neural Network from scratch
Are you someone who is always fond of using machine learning and deep learning libraries such as Scikitlearn, TensorFlow, PyTorch, etc, but don’t really understand how a neural network works underneath the libraries? If so, this post tries its best to explain what a neural network is, how it works,...