PyData Tel Aviv Meetup: Visualizing High Dimensional Data (t-SNE) - Gal Yona

Many of us are used to think about data visualization as creating simple 2-variable plots to accompany our slides. In practice, this is hardly the case. I claim that in today's ML landscape - rich with complicated (and often uninterpretable) models, and usually very high dimensional data - good knowledge of data visualization techniques is a crucial tool for any serious practitioner. Like many other concepts in ML, while applying these techniques is usually easy (no more than 2-3 lines in Python) - truly understanding what's going on in the background, and coming up with useful applications, is a much more challenging task. In the first part of the talk, I'll give a short introduction to t-SNE - a beautiful algorithm and more importantly, the state of the art approach to visualizing high dimensional data. We'll talk about how it differs from simple dimensionality reduction techniques (like PCA) and give some intuition into why it usually performs very well. In the second part I'll mention two example applications that will hopefully spark your interest and creativity. The first application is arranging a huge collection of images by their visual similarity in an unsupervised approach. I will focus on some practical challenges I ran into while trying to efficiently implement this solution. The second application is revolves around visualizing the representations learnt by a neural network in order to better understand what is bases its predictions on. It shows how visualization can play a role in the task of "peeking" into the Deep Learning black box.

PyData Tel Aviv Meetup #6
10 August 2017
Sponsored by Oracle
https://www.meetup.com/PyData-Tel-Aviv/

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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

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