...by developing a machine learning spam classifier. The process is part of an upgrade to the whole user feedback pipeline at GOV.UK, aiming to put critical insights in the hands...
...user has left us some comments, but there is not enough information to allow us to classify it as either 'ok' or one of the other classes. Machine learning and...
...and the public sector. Machine Learning is a method for creating algorithms that enable computers to learn from data to make predictions. Examples of machine learning techniques are; reinforcement learning,...
...used supervised machine learning Supervised machine learning is an algorithm that learns patterns from a sample of data that has already been classified, so it can use them to classify...
...running machine learning The first choice we had to make was how we’d host the node2vec machine learning algorithm. Many cloud providers offer what’s called a virtual machine, which –...
...scientist’s time. Instead, we try to focus on applying machine learning to existing products and services where it has matured to the point where machine learning and AI can usefully...
...app using Python’s Django library to help his colleagues at the Education Funding Agency prioritise resources. Using machine learning, the app predicts financial and governance risks associated with an Academy...
...at identifying patterns in text datasets. On the day, 2 data scientists spoke about their use of unsupervised machine learning to help them. This is when a computer is used...
...brilliantly clear online textbook. There is also a good CodeAcademy Python course. Machine Learning Data Scientists often use a range of modern statistical techniques called machine learning. It’s extremely important...
...techniques to obscure sensitive or private information in datasets. These include statistical methods, deep learning techniques and natural language processing for the data types above. Typically they can be summarised...
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