As a data scientist, you have been working on a model for several weeks, and the metrics you defined as success criteria now look promising. You want to put your model into a production environment and wonder what you should do next. When it comes to productionizing machine learning models…

It has been a long time since a degree was enough to strive in life, now things are way different from when obtaining a bachelor’s degree was a guarantee of a wealthy life, right now the essential skill everyone has to master is the ability to learn. …

Exploratory Data Analysis (EDA) is the first stage of any data science project. By exploring and analyzing datasets we can summarize their main characteristics, recognize hidden patterns, and prepare them for further processing. To perform an EDA we usually rely on Jupyter Notebooks, which is a web-based environment, within them…

Data scientists and machine learning engineers have to solve problems by relying on their ability to manipulate, transform, and process data. This can be done using a different set of skills and tools. Jupyter Notebooks One of the most common tools used by data scientists is the Jupyter Notebook. These are files…

In this post, I am going to talk about the different metrics that we can use to measure classifier performance when we are dealing with unbalanced data. Before defining any metric let’s talk a little bit about what an unbalanced dataset is, and the problems we might face when dealing…

In this post, I will extend the general idea of autoencoders to develop a convolutional autoencoder. This post is a continuation of this article, in which I explained the main idea behind autoencoders and their architecture. …

In this article I am going to delve into the possible applications and architectures that auto encoders can have, and how to implement them using TensorFlow and Keras. Autoencoders… The definition. Autoencoders play a fundamental role in unsupervised learning and in deep learning architectures for transfer learning and other tasks. Broadly, they are…

How we can use Process Mining techniques to reveal the processes behind organizational data using Python. — In this post, I am going to explore how we can use Process Mining techniques to reveal the processes behind organizational data. …

The easiest way to create a web user interface for your model. — During the lifecycle of a machine learning project, data scientists have to overcome different challenges related to the nature of the problem, and many times most of the models developed never see the light of the day. In addition to these scenarios, data scientists are usually less versed in topics…