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#machine learning

Where the concept of sampling began

Are you stuck in the past? A case against data sampling Part I

Increasingly large and diverse data sets allow us to form complex insights. With all this data, why would we limit ourselves by using data sampling instead? Sampling only works when it is put in the hands of data science specialists. In this article, learn about some of the downsides of using data sampling and how it limits and undermines business decisions. Read part one of the case against data sampling.

Laying the groundwork for big data

Building a data platform on Google Cloud Platform

At the moment, big data is very popular and there is a wide variety of products available for handling data. In this article, read a case study about a German startup tackled their data problems and built a common data platform into their architecture. The data platform consists of four components: Ingestion, storage, process, and provisioning.

Data-powered solutions

How will AI impact the e-commerce industry?

Artificial intelligence and machine learning are changing many industries, including e-commerce. This article examines some of the biggest trends in e-commerce that have appeared thanks to the growing use of AI technologies. Using these technologies can set your enterprise ahead of the competition and give you the edge you need.

Watch Thiago da Silva Alves and Jean Metz's Machine Learning Conference 2019 session

Honey bee conservation using deep learning

Honey bee colony assessment is usually carried out via the laborious manual task of counting and classifying comb cells. Beekeepers perform this task many times throughout the year to asses the colony’s strength and to track its development. As you can imagine, this is an extremely time-consuming and error-prone task.

Tips from tech giants

What Twitter and Facebook can teach us about machine learning

What lessons can Twitter and Facebook teach us about machine learning? These tech giants provide some ‘what to do’s, and even some ‘what not to do’s. Keep these important tips and practices in mind in order to improve your business model. Make sure you don’t forget about the end users’ experience and strive towards the best result.