Understanding Expectation-Maximization (EM) algorithm with an example in Python

7 mins read Suppose we have some data sampled from two different groups, red and blue: Here, we can see which data point […]

Using pre-commit and Makefile for Python code development workflow

5 mins read Introduction When developing Python code we are constantly adding and committing changes. However, nothing stops us from committing low-quality code, e.g. code […]

Machine Learning From Scratch Series: Naive Bayes and Gaussian Naive Bayes

16 mins read Introduction Naïve Bayes algorithm is a supervised classification algorithm based on the Bayes theorem with strong (Naïve) independence among features. In machine learning and data […]

Making data pipelines in Pandas using .pipe() method

13 mins read Real-life data is usually messy. It requires a lot of preprocessing to be ready for use. Pandas being one of […]

23 Useful but less used Pandas Functions

11 mins read Pandas is so vast and deep that it enables you to execute virtually any tabular manipulation you can think of. […]

Hands-on Docker Swarm networking using Play with Docker

11 mins read In this article, I’m going to cover 2 main subjects of the networking domain for the Docker Certified Associate DCA […]

The BERT Model

17 mins read The year 2018 has been an inflection point for machine learning models handling text (or more accurately, Natural Language Processing […]

Definitive Docker Swarm Tutorial

17 mins read In this guide, you will learn everything you need to know about Docker Swarm and how to use it to […]

Using BERT for Sentence Sentiment Classification

11 mins read Progress has been rapidly accelerating in machine learning models that process language over the last couple of years. This progress […]

Seq2Seq models, Attention Mechanism, and Transformers Explained

29 mins read Sequence-to-sequence models are deep learning models that have achieved a lot of success in tasks like machine translation, text summarization, […]

Volumes in Docker Compose tutorial

5 mins read The purpose of this post is to review how we can use volumes in Docker Compose. These are some possible scenarios: […]

A guide on Gradient Boosting models

22 mins read An introduction to additive modeling Before we get into boosting, let’s look at an example of what mathematicians call additive modeling because […]

What are Digests in Docker

6 mins read Most Docker images are run as containers by invoking something along the lines of docker run <image>:<tag>. However, it’s also possible–and […]

ARCH and GARCH models for Time Series Prediction in Python

11 mins read A change in the variance or volatility over time can cause problems when modeling time series with classical methods like […]

Finding and removing seasonality in Time-Series Data with Python

17 mins read Seasonality in Time Series Time series data may contain seasonal variation. Seasonal variation, or seasonality, are cycles that repeat regularly […]

ARIMA and SARIMA for Real-World Time Series Forecasting in Python

15 mins read Time series and forecasting have been some of the key problems in statistics and Data Science. Data becomes a time […]

A review of techniques for Time Series prediction

43 mins read Working with time series data? Here’s a guide for you. In this article, you will learn how to compare and […]

Building faster and smaller docker images with multistage DockerFile builds

5 mins read There is no doubt about the fact that Docker makes it very easy to deploy multiple applications on a single […]

Difference between CMD and ENTRYPOINT Commands in Dockerfile

14 mins read Introduction Containers are designed for running specific tasks and processes, not for hosting operating systems. You create a container to serve […]

Docker Shell and Exec Form difference

4 mins read The RUN, ENTRYPOINT, and CMD, instructions all have two different forms they can be written in, and those forms change how each of […]