Ovidiu Mățan: You have been leading Bosch Engineering Center Cluj for a few months now. How was the transition into your new role, and how do you see the integration of the technologies developed in Cluj into the Bosch global ecosystem?

Frank Wolf: I took over the role of Head of Bosch Engineering Center Cluj this year in July, and since then I am responsible for leading this great organization with more than 800 employees and about 200 interns.

At the end of the first part of the series we had a preprocessing pipeline ready to load data and concatenate the features selected for the training into one special feature called Features, and a target feature named Label serving as a category where the selected feature classifies.

Data being the most valuable commodity nowadays, it lies at the core of almost every business, irrespective of its domain. Whether we’re talking about search engines, entertainment platforms, ecommerce stores or fintech solutions, they are all about data and represent it in the most meaningful way to their users. In the process of gathering these vast amounts of data, many organizations are leveraging web scraping to extract information from 3rd party sources, such as websites. In most cases, the existing information on these websites is designed for human end-users.

Six years ago, I started to work on the first microservices projects. It was a migration from a monolithic solution to something different, to containers and microservices. Fast forward, we are in 2020, and in ALL engagements where I am involved, we have containers and something more – serverless.

The purpose of these series of articles is to provide a complete guide (from data to predictions) to machine learning, for .NET developers in a .NET ecosystem, and that is possible now using Microsoft ML.NET and Jupyter Notebooks. Moreover, you don't have to be a data scientist to do machine learning.

The right product meets the customer needs by addressing solutions to their problems, while keeping them engaged to use and always ask for more. Some of the most asked questions on this challenge would be how we can validate our product to meet the needs of our customers, what the next step or investment is, how we can validate our choices and lastly, the most important one, how we can build the right product. All these questions will be tackled in our article.