Education
Hosted by Edderic Ugaddan, Apurva Naik, Alex Au · Education · EN
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.
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Contact path
Verified email
Booking probability
17%
Guest openness
Selective
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Signup to Generate a PitchStartup 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.
Startup Data Science is hosted by Edderic Ugaddan, Apurva Naik, Alex Au. The show has published 5 episodes to date.
Recent episodes include "Episode 010 - Lesson 5 - Part 1 (Practical Deep Learning for Coders)" (8 September 2017), "Episode 009 - Lesson 4 - Part 2 (Practical Deep Learning for Coders)" (9 July 2017), and "Episode 008 - Lesson 4 - Part 1 (Practical Deep Learning for Coders)" (8 July 2017).
Startup Data Science publishes roughly daily across 5 episodes.
Booking probability for Startup Data Science is 17%, and the host is rated Selective on guests. Startup Data Science requires a Pod Score of 80 or higher. Startup Data Science's contact route on record: verified email.
The strongest fits for Startup Data Science are Business & Professional Training. Startup Data Science has an education audience.
Edderic Ugaddan, Apurva Naik, Alex Au hosts Startup Data Science, an education podcast with 5 episodes published.
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Startup Data Science
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...
Startup Data Science
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...
Startup Data Science
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...
Startup Data Science
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"...
Startup Data Science
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...
Startup Data Science
Apurva feels impressed because for complex tasks like image classification, "simple" things like linear regression is sometimes good enough. Alex and Edderic warn listeners to basically allocate more time to this...
Startup Data Science
Alex Au, Apurva Naik, and Edderic Ugaddan discuss the first part of Lesson 2 of Practical Deep Learning for Coders. Apurva and Alex talks about feeling that the segue-way between lesson 1 and 2 was not smooth. For...
Startup Data Science
Alex Au, Apurva Naik, and Edderic Ugaddan discuss what it's like to go through the setting up for AWS instance so that they could run the 7 lines of code that abstracted the VGG model, which had best-in-class...
Startup Data Science
Apurva Naik, Alex Au, and Edderic Ugaddan discuss the first half of the Lesson 1 of Practical Deep Learning for Coders (http://course.fast.ai/lessons/lesson1.html). We discuss what we find difficult, what we are excited...
Startup Data Science
In Episode 0, Alex Au, Apurva Nalik, and Edderic Ugaddan introduce themselves, talk about their background, why they wanted to get into Data Science, and what the format of the podcast is generally going to be.
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