Machine Learning

Machine Learning

Introduction

Set up in 2017, the LSESU Machine Learning Society aims to increase the LSE community’s understanding of machine learning, its potential applications and equip members with relevant competencies.

With the increased availability of large data sets and the importance of predicting outcomes rather than just explaining them in the social sciences, Machine Learning is starting to become a popular tool. However, both the theory and application of Machine Learning methods remains detached from the research and teaching we are exposed to. The reason is that it requires some practical understanding of Computer Science techniques and mathematical intuition for statistical learning theory. This society aims at addressing the broadening interface between ML and social science by empowering students with the right tools to be able to understand and deploy ML methods to solve their data driven questions.

The main goals of the society are as follows:

a. Equip LSE students with basic programming competencies and statistics knowledge necessary for Machine Learning

b. Increase the understanding of Machine Learning methods and their intersection with various Social Scientific Applications such as but not limited to Econometrics and Text Analysis

c. Develop students’ critical thinking ability through adopting a data scientist’s logical framework

d.  Provide LSE students with opportunities to engage with practitioners and enhance their exposure to real-world industry use-cases of machine learning

 

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