When we try to divide machine learning methods, we generally tend to separate them into two fundamentally different groups: supervised and unsupervised. So, where do semi-supervised methods fit in?...

# Enhance your CNN Networks with Squeeze and Excitation (SE) blocks: Attention Mechanism for Input Channels

We know that Convolutional Neural Networks (CNNs) are very popular when it comes to capturing specific properties of an image that are most salient for a given task. In fact, most of the research h...

# An Overview of Research in Video Description in 2020

The following post is greatly inspired by the paper Video Description: A Survey of Methods, Datasets and Evaluation Metrics. I have tried to summarize the research that has been undergone in the fi...

# 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 outp...

# 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 ...

# 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 t...

# 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 “d...

# Implementation of a Neural Network from scratch

Are you someone who is always fond of using machine learning and deep learning libraries such as Scikit-learn, TensorFlow, PyTorch, etc, but don’t really understand how a neural network works under...

# Neural Network Basics with Logistic Regression

These are some of my notes taken from the first course of Deep Learning Specialization (Neural Networks and Deep Learning) by deeplearning.ai. This might help you gain insights on how a neural netw...

# RandomForest with scikit-learn - Part 2

Welcome to the second part of the post. In this half, we will be implementing RandomForest regressor on our own dataset. For that first, you will need to have a dataset. The one that I used is a we...