Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems
(This is a blogpost version of a talk I gave at MLConf SF 11/14/2014. See below for original video and slides)
- recommender systems 9
- machine learning 3
- research 2
- explicit feedback 2
- netflix 2
- big data 2
- models 2
- conferences 1
- presentation skills 1
- game dynamics 1
- quora 1
- Social Networks 1
- trust 1
- agile 1
- extreme Programming 1
- mamagement 1
- scrum 1
- noise 1
- error 1
- stats 1
- explicit 1
- implicit 1
- music recommenders 1
- user modeling 1
- interaction 1
- presentation data 1
- conference 1
- recsys11 1
- netflix prize 1
- recsys 1
- software 1
recommender systems
Introduction to Recommender Systems: A 4-hour lecture
A couple of weeks ago, I gave a 4 hour lecture on Recommender Systems at the 2014 Machine Learning Summer School at CMU. The school was organized by Alex Smola and Zico Kolter and, judging by the a...
Beyond the 5 Stars Round up
Last week, I published a post on the Netflix tech blog. The post, entitled “Netflix Recommendations: Beyond the 5 stars” describes how recommendations have evolved at Netflix since the Netflix Priz...
Recsys 2011 – Notes and Pointers
I found Recsys this year of very high quality in general. There were many good papers and presentations. The Industry track was also very high-quality, with very interesting talks from companies s...
The Recommender Problem & the Presentation Context
In the traditional formulation of the “Recommender Problem”, we have pairs of items and users and user feedback values for very few of those dyads. The problem is formulated as the finding of a uti...
Joining Netflix
Three weeks ago, I started to work for Netflix. Everything has moved so fast with so many things to do and learn that it seems like I have already been here for a much longer time!
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
Recommender Systems: We’re doing it (all) wrong
A few days back, there was an interesting post by Judy Robertson in the Communications of the ACM blog. The post, entitled “Stats: We’re doing it wrong“, builds upon a paper from last year’s CHI co...
The Science and the Magic of User Feedback
That was the main title of a series of talks I gave in different labs and companies during my recent California tour. In this presentation, I talked about many of our recent projects related to how...
machine learning
Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems
(This is a blogpost version of a talk I gave at MLConf SF 11/14/2014. See below for original video and slides)
Introduction to Recommender Systems: A 4-hour lecture
A couple of weeks ago, I gave a 4 hour lecture on Recommender Systems at the 2014 Machine Learning Summer School at CMU. The school was organized by Alex Smola and Zico Kolter and, judging by the a...
More data or better models?
The discussion of whether it is better to focus on building better algorithms or getting more data is by no means new. But, it is really catching on lately. This was one of the preferred discussion...
research
Managing Research the Agile Way
I have discussed previously on this blog about how well the Scientific Method adapts to Agile approaches. These ideas also took me to an unfinished effort to draft an Agile Research Manifesto. Howe...
Did you prepare your talk?
I don’t consider myself to be a great presenter. As a matter of fact, every time I finish a presentation, I find myself thinking about how many things I screwed up and could have done much better. ...
explicit feedback
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
The Science and the Magic of User Feedback
That was the main title of a series of talks I gave in different labs and companies during my recent California tour. In this presentation, I talked about many of our recent projects related to how...
netflix
Beyond the 5 Stars Round up
Last week, I published a post on the Netflix tech blog. The post, entitled “Netflix Recommendations: Beyond the 5 stars” describes how recommendations have evolved at Netflix since the Netflix Priz...
Joining Netflix
Three weeks ago, I started to work for Netflix. Everything has moved so fast with so many things to do and learn that it seems like I have already been here for a much longer time!
big data
Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems
(This is a blogpost version of a talk I gave at MLConf SF 11/14/2014. See below for original video and slides)
More data or better models?
The discussion of whether it is better to focus on building better algorithms or getting more data is by no means new. But, it is really catching on lately. This was one of the preferred discussion...
models
Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems
(This is a blogpost version of a talk I gave at MLConf SF 11/14/2014. See below for original video and slides)
More data or better models?
The discussion of whether it is better to focus on building better algorithms or getting more data is by no means new. But, it is really catching on lately. This was one of the preferred discussion...
conferences
Did you prepare your talk?
I don’t consider myself to be a great presenter. As a matter of fact, every time I finish a presentation, I find myself thinking about how many things I screwed up and could have done much better. ...
presentation skills
Did you prepare your talk?
I don’t consider myself to be a great presenter. As a matter of fact, every time I finish a presentation, I find myself thinking about how many things I screwed up and could have done much better. ...
game dynamics
On Trust Networks and Gamification. Or How Quora can overcome its Hype and embrace long-term Success
If you are reading this blog I am pretty sure that you know quite a lot about Quora by now. If not, you should sign on and try it a bit before you continue reading the post.
quora
On Trust Networks and Gamification. Or How Quora can overcome its Hype and embrace long-term Success
If you are reading this blog I am pretty sure that you know quite a lot about Quora by now. If not, you should sign on and try it a bit before you continue reading the post.
trust
On Trust Networks and Gamification. Or How Quora can overcome its Hype and embrace long-term Success
If you are reading this blog I am pretty sure that you know quite a lot about Quora by now. If not, you should sign on and try it a bit before you continue reading the post.
agile
Managing Research the Agile Way
I have discussed previously on this blog about how well the Scientific Method adapts to Agile approaches. These ideas also took me to an unfinished effort to draft an Agile Research Manifesto. Howe...
extreme Programming
Managing Research the Agile Way
I have discussed previously on this blog about how well the Scientific Method adapts to Agile approaches. These ideas also took me to an unfinished effort to draft an Agile Research Manifesto. Howe...
mamagement
Managing Research the Agile Way
I have discussed previously on this blog about how well the Scientific Method adapts to Agile approaches. These ideas also took me to an unfinished effort to draft an Agile Research Manifesto. Howe...
scrum
Managing Research the Agile Way
I have discussed previously on this blog about how well the Scientific Method adapts to Agile approaches. These ideas also took me to an unfinished effort to draft an Agile Research Manifesto. Howe...
noise
The Science and the Magic of User Feedback
That was the main title of a series of talks I gave in different labs and companies during my recent California tour. In this presentation, I talked about many of our recent projects related to how...
error
Recommender Systems: We’re doing it (all) wrong
A few days back, there was an interesting post by Judy Robertson in the Communications of the ACM blog. The post, entitled “Stats: We’re doing it wrong“, builds upon a paper from last year’s CHI co...
stats
Recommender Systems: We’re doing it (all) wrong
A few days back, there was an interesting post by Judy Robertson in the Communications of the ACM blog. The post, entitled “Stats: We’re doing it wrong“, builds upon a paper from last year’s CHI co...
explicit
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
implicit
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
music recommenders
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
user modeling
Walk the Talk: On the Combination of Implicit and Explicit Feedback
Last week, Denis Parra presented our paper entitled “Walk the Talk: Analyzing the Relation between Implicit and Explicit Feedback for Preference Elicitation” at the UMAP conference. The paper won D...
interaction
The Recommender Problem & the Presentation Context
In the traditional formulation of the “Recommender Problem”, we have pairs of items and users and user feedback values for very few of those dyads. The problem is formulated as the finding of a uti...
presentation data
The Recommender Problem & the Presentation Context
In the traditional formulation of the “Recommender Problem”, we have pairs of items and users and user feedback values for very few of those dyads. The problem is formulated as the finding of a uti...
conference
Recsys 2011 – Notes and Pointers
I found Recsys this year of very high quality in general. There were many good papers and presentations. The Industry track was also very high-quality, with very interesting talks from companies s...
recsys11
Recsys 2011 – Notes and Pointers
I found Recsys this year of very high quality in general. There were many good papers and presentations. The Industry track was also very high-quality, with very interesting talks from companies s...
netflix prize
Beyond the 5 Stars Round up
Last week, I published a post on the Netflix tech blog. The post, entitled “Netflix Recommendations: Beyond the 5 stars” describes how recommendations have evolved at Netflix since the Netflix Priz...
recsys
Introduction to Recommender Systems: A 4-hour lecture
A couple of weeks ago, I gave a 4 hour lecture on Recommender Systems at the 2014 Machine Learning Summer School at CMU. The school was organized by Alex Smola and Zico Kolter and, judging by the a...
software
Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems
(This is a blogpost version of a talk I gave at MLConf SF 11/14/2014. See below for original video and slides)
Social Networks
On Trust Networks and Gamification. Or How Quora can overcome its Hype and embrace long-term Success
5 minute read
If you are reading this blog I am pretty sure that you know quite a lot about Quora by now. If not, you should sign on and try it a bit before you continue reading the post.