Xomnia is a word combining the letter ‘X’ – the unknown – and “Omnia” – Latin for everything. Our team of data scientists and big data engineers are trained to find the undefined – X – in all the relevant data sources – Omnia. This unknown – X – is untapped business value. Combining the X and Omnia you get the Xomnia spirit. Eager, curious and dedicated people, who have the belief that the future is big data.
So, you’ve got some text mining experience under your belt? We’re here to take you to the next level! Now that you’ve applied text classification techniques to solve well-known challenges such as sentiment analysis and topic classification, it’s time to dive into unsupervised models. Using these advanced techniques, we may discover new topics in a dataset, or identify different types of customers by analyzing email interactions.
This course will teach you how to apply unsupervised learning techniques to extract information from unlabeled text data. You will learn how to perform document clustering and topic modeling, and visualize and interpret your results. You will also learn about word vectors and apply some state-of-the-art text mining algorithms based on neural networks. At the end of this training, you should have a full arsenal of techniques to approach any text mining problem.
Requirements: The course assumes some experience with text preprocessing and with text classification in Python’s scikit-learn. You should also possess basic knowledge on generic unsupervised learning techniques.