Jorge Davila­ Chacon
Machine Learning Tech

Data and AI Innovators – Jorge Davila­ Chacon

Jorge Davila­ Chacon discussed the RL application for debt collection at Data Innovation Summit 2017. But a time-lapse of almost 3 years is a lifetime in the machine learning world. This was the reason we invited Jorge to talk about recent developments in AI and ML, and particularly in reinforcement learning, not only from a technical side, but also from a social aspect of the adoption of these technologies.

Daniel Zakrisson
Machine Learning Tech

Data and AI Innovators – Daniel Zakrisson

Giving up ownership over their data even for collaboration for building machine learning models is what organisations fret about. Daniel Zakrisson talked about federated machine learning as a solution for this predicament at Data Innovation Summit 2019.

Gesture recognition
Machine Learning Tech

ML codes can open iron doors: Gesture recognition

Electronic access cards are nothing new – last century news. But what if you could open a door just by making a wrist with your phone. A group of very smart guys sat down and decided to find a way to take the experience of opening a door to the next level – and the perfect solution was to turn the phone into a key relying on gesture recognition.

diversity
Advance Analytics Artificial Intelligence Business Data Science Deep Learning Machine Learning Popular

We need to talk about diversity in data (part 1)

In the month leading to the second edition of the event that brings together women data practitioners to discuss accelerating data and AI innovation in the organisation, we talked to our speakers on the subject of diversity and the importance of initiatives that encourage more female engagement in the tech and data fields. But we also asked them about their personal experience and decision to start a career in data.

newspaper
Artificial Intelligence Business Machine Learning

Newspapers need recommendation systems: The Telegraph Case Study

We might not be aware of it, but recommendation systems influence everything we read, watch and buy online. Every website has a recommendation system built in the background whether it’s to suggest an item based on what we have bought previously, suggest the next song to play, all the way to suggested jobs based on our qualifications on LinkedIn, or even dating websites matching us with potential partners.

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