Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Deep learning for fonts

14:0514:45 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 17
Secondary topics:  Deep Learning
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Artists, engineers, and product managers



Prerequisite knowledge

  • A basic understanding of machine learning

What you'll learn

  • Learn how to apply deep learning to offbeat topics and the fastest way to test deep learning on any topic


2016. It was a sunny morning in London, and Nischal Harohalli Padmanabha and Raghotham Sripadraj were speaking about deep learning at PyData London. Of all the things they saw that day, there was this one thing they were super curious to know: what is the font on the boards of London’s buses?

It was one of the most legible, crispest, and cleanest fonts they had ever seen. They quickly googled to figure out it was Johnston. That was easy. However, they soon began to notices a lot of instances where couldn’t determine the font so easily. Then, the big idea. Given that they are deep learning practitioners, why not use it to classify fonts? Why not have an app where you can point at an image of text and it tells you the font? Hold on! Maybe someone had already thought about this. A quick search shows two good options: Font Squirrel and What the Font. But it turns out that the results are not as expected with those apps, so Nischal and Raghotham decided to build something better: Fontastic.

Nischal and Raghotham share their experience of building a deep learning classifier with as little data as possible.

Topics include:

  • Data acquisition techniques
  • Data augmentation techniques used to generate more data and increase generalization of models
  • Determining how two or more fonts are similar
  • Which frameworks and libraries can get you the best baseline results
  • How to expose the classifier as an API
Photo of Raghotham Sripadraj

Raghotham Sripadraj



Photo of Nischal Harohalli Padmanabha

Nischal Harohalli Padmanabha


Nischal HP is the vice president of engineering at Berlin-based AI startup omnius, which builds AI products for the insurance industry. Nischal is also a mentor for data science on Springboard. Previously, he was a cofounder and data scientist at Unnati Data Labs, where he helped build end-to-end data science systems in the fields of fintech, marketing analytics, event management, and medicine. During his tenure at former companies like Redmart and SAP, he was involved in architecting and building software for ecommerce systems in catalog management, recommendation engines, sentiment analyzers, data crawling frameworks, intention mining systems, and gamification of technical indicators for algorithmic trading platforms. Nischal has conducted workshops in the field of deep learning and has spoken at a number of data science conferences like the Strata Data Conference in San Jose 2017, PyData London 2016, PyCon Czech Republic 2015, The Fifth Elephant India (2015 and 2016), and Anthill Bangalore 2016. He’s a strong believer in open source and loves to architect big, fast, and reliable AI systems. In his free time, he enjoys traveling with his significant other, music, and grokking the web.

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Picture of Raghotham Sripadraj
Raghotham Sripadraj | SENIOR DATA SCIENTIST
15/05/2019 11:49 BST

Here are the slides –

3/05/2019 12:05 BST

Are the talk’s slides available?