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| Title | Practice Session (Part 1) - Meetup for Machine Learning in Quantitative Finance |
| Time | 19:00 – 20:30, July 25, 2018 |
| Venue | Room 12, the 16th Floor CGC1, Citigroup building, Canary Wharf, 25 Canada Square, London, E14 5LB |
| Content | In this event, we will host a practice session on the implementation of supervised learning algorithms with the focus on artificial neural network. Scikit-Learn is an efficient Python tool for data mining and data analysis while Keras is a high-level neural networks API written in Python. This practice session aims to equip the participants with the hands-on experience in supervised learning with the above-mentioned popular Python packages.Dr Hao Ni will give a presentation based on the Google Colaboratory Python demo in order to(1) show the pipelines for solving data classification problems, including how to load the data, train and validate a model;(2) and articulate the key aspects of fine tuning artificial neural network to empirical datasets.You will be amazed by that all are done by just few lines of Python code. We will concentrate on the MNIST dataset (classification of digits) as a concrete working example. We expect all participants bring their laptops to the session and follow the instructions to work through the working examples and play with the datasets by themselves. After the session, the participants are expected to independently(1) Implement the pipelines of classification algorithms using Scikit-Learn;(2) Apply the artificial neural network to classification problems using Keras,Link password:MachineLearningQuantFinance1 |
| URL | Page Link |