Custom Machine Learning Models

Waste Reduction with parameter optimization: 33% failure reduction for leading technical yarn Manufacturer

Resultance is an international mid-sized advisory firm and partners with Faktion for the delivery of A.I. projects.
Together with Faktion, we helped one of their clients to find ways of increasing material yield in their manufacturing and production lines. Due to parameter optimization, the project resulted in a successful prediction model, able to reduce waste significantly without the need of interfering with the live production process.

Bridging the gap between academic AI data research and business applications

Howest & Faktion announce an exclusive partnership to amplify knowledge validation and talent transfer. The partnership strives to boost both partners’ efforts to deliver market-driven and applied research in the field of AI & Data Science. By this talent & knowledge exchange, the partnership brings much-needed collaboration between the academic and the business world for SMEs and large multinationals.

How AI Transforms Financial Services

With the global artificial intelligence (AI) market expected to be at almost $60 billion by 2025, many applications transform everyday life. Organizations seek ways to sustain their competitiveness in the marketplace by using AI to power what people see online, purchase products, and provide personal recommendations. As consumers realize the benefits of AI to them, they are more willing to share personal data, giving businesses a fantastic opportunity to innovate.

Jane allows elders to stay at home longer

The Jane smart alert system has matured through several iterations with testers providing invaluable feedback that allowed the system to reach the accuracy it has today.

The Tyranny of the mean

While simple in nature, averages are tricky and deceptive when misused, the variance in your data is a treasure!

DATABRICKS: The Glue We Were Missing

When you throw a fresh dataset at a Python data scientist the first thing he or she will do is spin up a Jupyter notebook and dig in. Notebooks offer you the freedom to run and tweak a block of code until you’re happy with it, add some nicely formatted documentation with a plot, and then move on to the next code block.

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