Startup Data Science

Edderic Ugaddan, Apurva Naik, Alex Au•soundcloud.com

Startup Data Science is the podcast where you learn startup-ready data science with programming basics. We discuss how to bootstrap data science techniques and understand their underlying mechanics by discussing open-source learning materials. Startup Data Science helps forward-thinking entrepreneurs, novice programmers, and seasoned software engineers to use Data Science to make a bigger impact.

Last refreshed: January 3rd, 2026 at 4:41 AM ⓘ

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Episodes

Episode 010 - Lesson 5 - Part 1 (Practical Deep Learning for Coders)

Alex gives a quick recap of Lesson 5, using embeddings with imdb review data to categorize movies into clusters using Natural Language Processing (NLP). Edderic, Apurva, and Alex discuss what they're excited about with using NLP and also speak to their motivation as they continue to learn deep learning.

Sep 08, 2017•32 min

Episode 009 - Lesson 4 - Part 2 (Practical Deep Learning for Coders)

Alex is excited about collaborative filtering and he could see using it in his startup to help people unlearn toxic behaviors and beliefs in a productive way. Apurva started working remotely; she found it hard to stay motivated to study. She has issues with collaborative filtering in Netflix; she feels like Netflix's recommendation algorithm is not good for discovering new things because she thinks the recommendations tend to be similar to the past. Edderic's been busy with work at Lingo Live. E...

Jul 09, 2017•26 min

Episode 008 - Lesson 4 - Part 1 (Practical Deep Learning for Coders)

Apurva loved Jeremy's presentation using Excel to show how calculations are being made; it was a great confidence-building exercise for her to replicate it in Excel. Edderic's excited about Jeremy's claim that Convolutional Neural Networks are doing well in Speech Recognition. There are tons of machine learning algorithms out there; he thinks it would be nice to have just one super algorithm/architecture to rule them all. Alex explains his idea of convolution through an analogy.

Jul 08, 2017•31 min

Episode 007 - Lesson 3 - Part 2 (Practical Deep Learning for Coders)

Alex thinks dropout is cool. He's still not quite sure what batch normalization is. Regarding ImageNet competition, Apurva, along with offering tips to staying motivated to learning says that instead of creating "new" models, people are only doing ensembling now to get a marginal edge over everyone else. Edderic announces revamping his PC workstation for deep learning (bye-bye Amazon!)

Jun 25, 2017•43 min

Episode 006 - Lesson 3 - Part 1 (Practical Deep Learning for Coders)

Alex promises to do 20 min. of Data Science every day to keep making progress. Edderic learns that Apurva hasn't submitted the Cats and Dogs Kaggle submission yet, so he feels a little bit better about himself for not submitting yet either. Alex mistakes Natural Language Processing for Neuro-Linguistic Programming (whoops!)

Jun 23, 2017•33 min

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