What is q-learning?

5 mins read Introduction One of my favorite algorithms that I learned while taking a reinforcement learning course was q-learning. Probably because it […]

What are Word Embeddings and how do they work? An introduction to Word2Vec (CBOW and Skip Gram)

22 mins read Word embedding is one of the most popular representations of document vocabulary. It is capable of capturing the context of […]

Implementing LSTM Networks in Python with Keras

27 mins read A powerful and popular recurrent neural network is the long short-term model network or LSTM. It is widely used because […]

How to reshape Input Data for Long Short-Term Memory (LSTM) Networks in Keras

9 mins read It can be difficult to understand how to prepare your sequence data for input to an LSTM model. Often there […]

A complete guide to understanding Long Short Term Memory (LSTM) Networks

37 mins read In this post, I provide three useful resources for understanding LTSMs. Introduction Sequence prediction problems have been around for a […]

Understanding L1 and L2 as Loss Function and Regularization

6 mins read While practicing machine learning, you may have come upon a choice of the mysterious L1 vs L2. Usually, the two […]

Different missing data mechanisms

3 mins read Missing data mechanisms concern the relationship between missing data and the values of variables in the data matrix. Given this focus, […]

Kernel Density Estimation (KDE) in Python

10 mins read Nonparametric Density Estimation In some cases, a data sample may not resemble a common probability distribution or cannot be easily […]

Implementations of Mutual Information (MI) and Entropy in Python

8 mins read In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual […]