Understanding Contiguous vs Non-Contiguous Tensors in PyTorch

13 mins read Tensor and View View uses the same data chunk from the original tensor, just a different way to ‘view’ its […]

Handling cyclical features, such as hours in a day, for machine learning pipelines with Python example

11 mins read What’s the difference between 23 and 1? If we’re talking about time, it’s 2. Hours of the day, days of […]

Understanding GloVe embedding with Tensorflow implementation

9 mins read In this article, you will learn about GloVe, a very powerful word vector learning technique. This article will focus on […]

Understanding Word2vec embedding with Tensorflow implementation

15 mins read This article is going to be about Word2vec algorithms. Word2vec algorithms output word vectors. Word vectors, underpin many of the […]

Minimal PyTorch LSTM example for regression and classification tasks

10 mins read The Idea Behind RNNs Recurrent neural networks in general maintain state information about data previously passed through the network. This […]

A complete guide to writing custom Datasets and DataLoader in PyTorch

19 mins read Table of Contents An Introduction To PyTorch Dataset and DataLoaderWhy Write Good Data Loaders and Datasets?The Basic PyTorch Dataset StructureImplementing […]

A guide to different Cross-Validation methods in Machine Learning

19 mins read In machine learning (ML), generalization usually refers to the ability of an algorithm to be effective across various inputs. It […]

Deep Reinforcement Learning: Using policy-based methods to play Pong from pixels

34 mins read This is a long-overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can […]

Automatic Differentiation Explained

8 mins read Introduction There are several methods to calculate gradients in computer programs: (1) Manual differentiation; (2) Symbolic differentiation; (3) Finite differences […]

Improvements in Deep Q-Learning with Python code: Dueling Double DQN, Prioritized Experience Replay, and Fixed Q-targets

28 mins read Deep Q-Learning was introduced in 2014. Since then, a lot of improvements have been made. So, today we’ll see four […]

A review of Deep learning based recommendation systems

20 mins read INTRODUCTION The number of research publications on deep learning-based recommendation systems has increased exponentially in the past recent years. In […]

Steps to setup Pytorch with GPU for NVIDIA GTX 960m (Asus VivoBook n552vw) in Ubuntu 16.4

2 mins read In this post, I’m gonna describe the steps I used to make Pytorch use GPU on my laptop. Generally, you […]

Restricted Boltzmann Machines (RBMs) Simply Explained

16 mins read Table of Content: Definition & Structure Reconstructions Probability Distributions Code Sample: Stacked RBMS Parameters & k Continuous RBMs Next Steps […]

Guidelines to use Transfer Learning in Convolutional Neural Networks

9 mins read Transfer learning involves taking a pre-trained neural network and adapting the neural network to a new, different data set. Depending […]

Dealing with imbalanced data in machine learning

8 mins read Imbalanced classes are a common problem in machine learning classification where there is a disproportionate ratio of observations in each […]