Sign up to save your podcasts
Or
Share The power of error analysis, tree models for search relevancy, what ChatGPT means for data scientists - Sergey Feldman - The Data Scientist Show #059
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
The power of error analysis, tree models for search relevancy, what ChatGPT means for data scientists - Sergey Feldman - The Data Scientist Show #059
Sergey Feldman is the head of AI at Alongside, providing mental health support for students. He is also a Lead Applied Research Scientist at Allen Institute for AI, where he built an ML model that improved search relevancy for scientific literature. Sergey has a PhD in Electrical and Electronics Engineering from the University of Washington. Today we’ll talk about machine learning for search, his consulting project for the Gates Foundation, AI for mental health, and career lessons. Make sure you listen till the end. If you like the show, subscribe, leave a comment, and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science.
Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's
Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/
Sergey's LinkedIn: https://www.linkedin.com/in/sergey-feldman-6b45074b/
Data Cowboys: http://www.data-cowboys.com/
Sergey Feldman: You Should Probably Be Doing Nested Cross-Validation | PyData Miami 2019: https://www.youtube.com/watch?v=DuDtXtKNpZs
December 4th, 2018 - Breakfast with WACh with Dr. Sergey Feldman, PhD: https://www.youtube.com/watch?v=vA_czRcCpvQ
(00:00:00) Introduction
(00:01:24) Machine learning skeptic
(00:03:02) Tree-based models for search relevance
(00:14:34) How to do error analysis
(00:19:20) Nested cross-validation
(00:21:34) Model evaluation
(00:30:43) Error analysis common mistakes
(00:33:37) How to avoid overfitting
(00:35:56) Consulting project with Gates Foundation
(00:41:16) Tree-based models vs linear models
(00:45:19) Working with non-tech stakeholders
(00:50:20) Chatbot for teen’s mental health
(00:54:32) Can ChatGPT provide therapy?
(00:58:12) How he got into machine learning
(01:02:12) How to not have a boss
(01:03:46) Feelings vs Facts
(01:09:02) Future of machine learning
(01:11:30) How to prepare for the future
(01:13:39) AutoML
(01:17:12) His passion for large language models
View all episodes
By Daliana Liu
4.7
7575 ratings
Sergey Feldman is the head of AI at Alongside, providing mental health support for students. He is also a Lead Applied Research Scientist at Allen Institute for AI, where he built an ML model that improved search relevancy for scientific literature. Sergey has a PhD in Electrical and Electronics Engineering from the University of Washington. Today we’ll talk about machine learning for search, his consulting project for the Gates Foundation, AI for mental health, and career lessons. Make sure you listen till the end. If you like the show, subscribe, leave a comment, and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science.
Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's
Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/
Sergey's LinkedIn: https://www.linkedin.com/in/sergey-feldman-6b45074b/
Data Cowboys: http://www.data-cowboys.com/
Sergey Feldman: You Should Probably Be Doing Nested Cross-Validation | PyData Miami 2019: https://www.youtube.com/watch?v=DuDtXtKNpZs
December 4th, 2018 - Breakfast with WACh with Dr. Sergey Feldman, PhD: https://www.youtube.com/watch?v=vA_czRcCpvQ
(00:00:00) Introduction
(00:01:24) Machine learning skeptic
(00:03:02) Tree-based models for search relevance
(00:14:34) How to do error analysis
(00:19:20) Nested cross-validation
(00:21:34) Model evaluation
(00:30:43) Error analysis common mistakes
(00:33:37) How to avoid overfitting
(00:35:56) Consulting project with Gates Foundation
(00:41:16) Tree-based models vs linear models
(00:45:19) Working with non-tech stakeholders
(00:50:20) Chatbot for teen’s mental health
(00:54:32) Can ChatGPT provide therapy?
(00:58:12) How he got into machine learning
(01:02:12) How to not have a boss
(01:03:46) Feelings vs Facts
(01:09:02) Future of machine learning
(01:11:30) How to prepare for the future
(01:13:39) AutoML
(01:17:12) His passion for large language models
More shows like Daliana's Game
View all
Bloomberg Intelligence
402 Listeners
a16z Podcast
1,036 Listeners
Data Skeptic
480 Listeners
Super Data Science: ML & AI Podcast with Jon Krohn
298 Listeners
DataFramed
267 Listeners
What's Next｜科技早知道
176 Listeners
硅谷101
184 Listeners
Last Week in AI
287 Listeners
All-In with Chamath, Jason, Sacks & Friedberg
9,207 Listeners
Big Technology Podcast
443 Listeners
No Priors: Artificial Intelligence | Technology | Startups
121 Listeners
This Day in AI Podcast
201 Listeners
VK科技閱讀時間
10 Listeners
BG2Pod with Brad Gerstner and Bill Gurley
461 Listeners
Training Data
43 Listeners