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Objectives

- Identify common tasks that industry has with textual data- Gain a practical understanding about advanced machine learning techniques for NLP- Acquire proficiency in implementing and creating NLP models for the above tasks- Learn how the fundamentals and cutting-edge machine learning approaches work together for performing text-related tasks in industry.

Who Should Attend

- Machine learning engineers- Data scientists- Data analysts

Entry Requirements

- Participants must successfully completed Text Analytics course offered by NUS-ISS.- Participants must have strong programming skills using Python, familiar with packages like Numpy, Pandas, Scikit-Learn, and well versed with Anaconda, Jupyter Notebook, and GitHub.- Participants must have sufficient background knowledge of machine learning and text mining, with experience building models from text data using common ML techniques(e.g. SVM, MLFF NN, etc.).- Participants must understand basic calculus to appreciate basic machine learning mathematics.- Participants must code /program/debug in the hands-on practical sessions.