Focus on the future: First annual Training Data Lab workshop

On 20 April, our Training Data Lab research group held its first annual online workshop, allowing our members to meet and share their research. Despite the distance, our meeting successfully allowed us to maintain the connection and dialogue between group members.

The day started with presenting the research group’s different ongoing projects. Our members shared their current and future research, which gave us an overview of the ongoing lines of work and how they relate to each other. The presentation of the projects was followed by a space for feedback and dialogue, which allowed us to share knowledge and experience among the group members.

In the second part of the workshop, our researcher Carla Cisternas provided training on our cloud-based labelling platform for training machine learning models. The training focused on the process of training data to train machine learning models, a crucial topic for any research using machine learning techniques.

Data training is a fundamental process for training machine learning models. It involves collecting and preparing large amounts of labelled data, which is then used to train a model to make predictions or decisions. The goal of data training is to create a robust and representative dataset that reflects the complexity and diversity of the problems you want to solve.

Carla Cisternas’ training taught us how to use our cloud-based tagging platform to automate the data training process. The platform allows us to collect, store and tag large amounts of data, which is especially useful when dealing with projects requiring extensive data for model training.

In sum, the first annual Training Data Lab workshop was a success. Our online meeting allowed us to maintain connection and dialogue between group members. At the same time, the training on our cloud-based labelling platform for training machine learning models provided a valuable opportunity to learn about the data training process.

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