This is part-5 of the case study on Boost Debt Collections and Recoveries using Machine Learning (MLBR). A machine learning predictive model to enhance the current recovery system by creating focus groups for business to boost debt collection.

The field of machine learning is becoming easier and easier to enter thanks to readily available tools, a wide range of open source datasets, and a community open to sharing ideas and giving advice. Almost everything you need to get started is online; it’…

What is pattern recognition, when and where is it used in machine learning? And how to train a pattern recognition system? Find out the answers in this post.

Image processing is a method to perform operations on an image to extract information from it or enhance it. Digital image processing…

Between 2015 and 2020 I have participated in Quantopian and Numerai tournaments. Being involved in these tournaments has led me to a very profitable journey: I made around $350k during these years.

We present a brief history of the field of interpretable machine learning (IML), give an overview of state-of-the-art interpretation methods, and discuss challenges. Research in IML has boomed in recent years. As young as the field is, it has over 200 yea…

Two of the world’s leading experts on algorithmic bias look back at the events of the past year and reflect on what we’ve learned, what we’re still grappling with, and how far we have to go.

Take the Survey for Machine Learning Operations (MLOps), it includes model deployment & management and data tracking, which helps productionizing ML models.

PIL stands for Python Image Library. In this article, we will look at its fork: Pillow. PIL has not been updated since…