Over the last 25 years, I have an unparalleled front seat to the digital transformation that is now accelerating in the connected manufacturing and automotive industry. Not many people have had the opportunity to witness the transformation and be as active in this area as I have; I consider myself lucky.

Most of us know the story of “The Tortoise and the Hare.” It is one of Aesop’s classic fables in which a speedy, overconfident hare becomes complacent and realizes, all too late, that the tortoise, although outmatched, has managed to beat him in a race. It teaches us lessons about overconfidence and perseverance and has caused phrases like “slow and steady wins the race” to creep into our everyday language.

“You cannot be the same, think the same and act the same if you hope to be successful in a world that does not remain the same.” This sentence by John C. Maxwell is so relevant to rapidly changing cloud hosting technology. Businesses understand the added value and are looking at cloud technologies to handle both operational and analytical workloads.

This blog post is a first of a series on how to leverage PyTorch’s ecosystem tools to easily jumpstart your ML / DL project. The first part of this blog describes common problems appearing when developing ML / DL solutions, and the second describes a simple image classification example demonstrating how to use Allegro Trains and PyTorch to address those problems.

Survival analysis is one of the most developed fields of statistical modeling, with many real-world applications. In the realm of mobile apps and games, retention is one of the initial focuses of the publisher once the app or game has been launched. And it remains a significant focus throughout most of the lifecycle of any endeavor.