Building a Test Collection for Event Detection Systems Evaluation

Before we start, if you’re not familiar with the Event Detection task in NLP you can refer to our previous post on this topic here. So you’ve built a system to detect events in the media… now what? While building a system is a key step, how the system performs on real-world data has equal importance. We need to know whether it actually works and if we can trust its decisions. So.. we need to evaluate our system before putting it in use. Evaluation is a highly important step in the development of any system type as it allows the … Continue reading Building a Test Collection for Event Detection Systems Evaluation

How to Version Control Your Machine Learning? – A Look into Data Version Control (DVC)

If you have spent time working with Machine Learning, one thing is clear: it’s an iterative process. Machine learning is about rapid experimentation and iteration, each experiment consists of different parts: the data you use, hyperparameters, learning algorithm, architecture, and the optimal combination of all of those Throughout this iterative process, your accuracy on your dataset will vary accordingly, and without keeping track of your experimenting history you won’t be able to learn much. Versioning lets you keep track of all of your experiments and their different components. How to Version Control ML Projects? One of the most popular ways … Continue reading How to Version Control Your Machine Learning? – A Look into Data Version Control (DVC)