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Transportation Modeling and Autonomous Vehicles With Matt Battifarano

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Manage episode 290955149 series 2881014
Konten disediakan oleh Travis Lawrence. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Travis Lawrence atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

In this episode, we speak with Matt Battifarano. Matt is a data scientist focusing on transportation modeling. He first started his career as a data scientist at a startup called Bridj where they created a smart micro-bus platform for urban transit similar to Uber Pool. Currently he’s working towards his PHD at Carnegie Mellon at their Mobility Data Analytics Center.
Top 3 Value Bombs:

  1. K.I.S.S - Keep it super simple. Do not over complicate the process, especially when just starting out prototyping..
  2. The importance of understanding the purpose/history of methods in AI/ML
  3. There are many challenges to developing autonomous vehicles - one in particular is creating an environment where you can test it safely. Unlike many AI/ML tests you cannot perform A/B tests with end users.
  continue reading

43 episode

Artwork
iconBagikan
 
Manage episode 290955149 series 2881014
Konten disediakan oleh Travis Lawrence. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh Travis Lawrence atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

In this episode, we speak with Matt Battifarano. Matt is a data scientist focusing on transportation modeling. He first started his career as a data scientist at a startup called Bridj where they created a smart micro-bus platform for urban transit similar to Uber Pool. Currently he’s working towards his PHD at Carnegie Mellon at their Mobility Data Analytics Center.
Top 3 Value Bombs:

  1. K.I.S.S - Keep it super simple. Do not over complicate the process, especially when just starting out prototyping..
  2. The importance of understanding the purpose/history of methods in AI/ML
  3. There are many challenges to developing autonomous vehicles - one in particular is creating an environment where you can test it safely. Unlike many AI/ML tests you cannot perform A/B tests with end users.
  continue reading

43 episode

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