Criteo Eng
Criteo Eng
  • 148
  • 151 905

zhlédnutí: 0

Video

Criteo DevXDays - How to have fewer incidents with Hexagonal Architecture32:47Criteo DevXDays - How to have fewer incidents with Hexagonal Architecture
Criteo DevXDays - How to have fewer incidents with Hexagonal Architecture
zhlédnutí 83Před měsícem
This talk was presented in our Criteo DevXDays 2023 edition. Hexagonal Architecture is a 20-year-old pattern ideally suited for implementing and maintaining APIs. Its primary objective is to completely isolate the core business logic from external dependencies, utilizing "ports" and "adapters" as connections to the outside world. At Criteo, several teams have adopted this architectural pattern....
Criteo DevXDays - Caring about our Public API23:30Criteo DevXDays - Caring about our Public API
Criteo DevXDays - Caring about our Public API
zhlédnutí 110Před 11 měsíci
This talk was presented in our Criteo DevXDays 2022 edition. The Criteo API empowers developers to programmatically build on the world’s largest advertising network. We have two lines of products: Marketing Solutions API and Retail Media API. Caring about external developers using your public API makes total sense. It affects your company strategy and reputation. Plus, making your API easier to...
Criteo DevXDays - BigDataFlow: Continuous Delivery of data pipelines29:00Criteo DevXDays - BigDataFlow: Continuous Delivery of data pipelines
Criteo DevXDays - BigDataFlow: Continuous Delivery of data pipelines
zhlédnutí 113Před 11 měsíci
This talk was presented in our Criteo DevXDays 2022 edition. Data at Criteo is a core asset and the source of reports we provide to both audiences, external and internal. We are talking about a massive amount of data daily and need a proper workflow management system to orchestrate every piece involved. After trying and experimenting with different solutions, an internal project started to crea...
Criteo DevXDays - Postman: from local tests to our Concourse CD pipeline22:12Criteo DevXDays - Postman: from local tests to our Concourse CD pipeline
Criteo DevXDays - Postman: from local tests to our Concourse CD pipeline
zhlédnutí 96Před rokem
This talk was presented in our Criteo DevXDays 2022 edition. Do you want to know how the Criteo API platform has leveraged Postman collection to implement continuous delivery? This is your talk :) Join us to discover how we use Postman, Newman and Concourse to set up an automation testing process for our APIs. You can also check the article here: medium.com/criteo-engineering/postman-from-local...
Criteo DevXDays - Efficient Testing Strategy in microservice era43:02Criteo DevXDays - Efficient Testing Strategy in microservice era
Criteo DevXDays - Efficient Testing Strategy in microservice era
zhlédnutí 229Před rokem
This talk was presented in our Criteo DevXDays 2022 edition. How do you face a good testing strategy in the microservice era? But, wait, do you even care about testing? We hope you do :) Let's face it, we learn about architecture, best practices, design patterns and other fancy developers' tools but testing strategy is left behind. Unless we are in a team where testing is a core value (e.g. thr...
Criteo DevXDays - GraalVM, Native Compilation on the JVM24:57Criteo DevXDays - GraalVM, Native Compilation on the JVM
Criteo DevXDays - GraalVM, Native Compilation on the JVM
zhlédnutí 83Před rokem
This talk was presented in our Criteo DevXDays 2022 edition. GraalVM has been all the hype recently in the Java community because of the native compilation it proposes. Native Java application means light packaging, instant startup, and low memory consumption: perfect for the cloud. Unsurprisingly, it’s now supported by all major frameworks (Spring Boot, Quarkus, Micronaut, …) This video will e...
Criteo DevXDays - What Developer Experience is and what we are doing about it31:03Criteo DevXDays - What Developer Experience is and what we are doing about it
Criteo DevXDays - What Developer Experience is and what we are doing about it
zhlédnutí 139Před rokem
This talk was presented in our Criteo DevXDays 2022 edition. If you are part of the developer circles, you probably heard a lot about developer experience in 2022. But is it really a new thing or just hype? What is it exactly, and what initiatives would help us? Why should we care? Please look at the video to find out the answers to those questions and how Criteo is surfing the Developer Experi...
Bob Carpenter - Pathfinder: Quasi-Newton Variational Inference1:15:42Bob Carpenter - Pathfinder: Quasi-Newton Variational Inference
Bob Carpenter - Pathfinder: Quasi-Newton Variational Inference
zhlédnutí 649Před rokem
Bob Carpenter - Pathfinder: Quasi-Newton Variational Inference
Jean Pachebat Accelerated Gradient Boosting with Higher Order Optimization Methods33:00Jean Pachebat Accelerated Gradient Boosting with Higher Order Optimization Methods
Jean Pachebat Accelerated Gradient Boosting with Higher Order Optimization Methods
zhlédnutí 158Před rokem
Jean Pachebat Accelerated Gradient Boosting with Higher Order Optimization Methods
Mingyuan Zhou - Adaptive Diffusion-based Deep Generative Models58:14Mingyuan Zhou - Adaptive Diffusion-based Deep Generative Models
Mingyuan Zhou - Adaptive Diffusion-based Deep Generative Models
zhlédnutí 164Před rokem
Mingyuan Zhou - Adaptive Diffusion-based Deep Generative Models
Darren Wilkinson - Compositional approaches to scalable Bayesian computation1:04:32Darren Wilkinson - Compositional approaches to scalable Bayesian computation
Darren Wilkinson - Compositional approaches to scalable Bayesian computation
zhlédnutí 178Před 2 lety
Darren Wilkinson - Compositional approaches to scalable Bayesian computation
Alexandre Gilotte - Learning From Aggregated Data1:01:48Alexandre Gilotte - Learning From Aggregated Data
Alexandre Gilotte - Learning From Aggregated Data
zhlédnutí 210Před 2 lety
Alexandre Gilotte - Learning From Aggregated Data
Arnaud Doucet : Diffusion Schrodinger Bridges - From Generative Modeling to Posterior Simulation1:09:32Arnaud Doucet : Diffusion Schrodinger Bridges - From Generative Modeling to Posterior Simulation
Arnaud Doucet : Diffusion Schrodinger Bridges - From Generative Modeling to Posterior Simulation
zhlédnutí 3,8KPřed 2 lety
Arnaud Doucet : Diffusion Schrodinger Bridges - From Generative Modeling to Posterior Simulation
Probabilistic Rank and Reward model - Project 4229:57Probabilistic Rank and Reward model - Project 42
Probabilistic Rank and Reward model - Project 42
zhlédnutí 185Před 2 lety
Probabilistic Rank and Reward model - Project 42
Christopher Sims - Large Parameter Spaces and Weighted Data: A Bayesian Perspective1:14:29Christopher Sims - Large Parameter Spaces and Weighted Data: A Bayesian Perspective
Christopher Sims - Large Parameter Spaces and Weighted Data: A Bayesian Perspective
zhlédnutí 275Před 2 lety
Christopher Sims - Large Parameter Spaces and Weighted Data: A Bayesian Perspective
Andrew Gelman - Bayesian Methods in Causal Inference and Decision Making1:15:27Andrew Gelman - Bayesian Methods in Causal Inference and Decision Making
Andrew Gelman - Bayesian Methods in Causal Inference and Decision Making
zhlédnutí 5KPřed 2 lety
Andrew Gelman - Bayesian Methods in Causal Inference and Decision Making
David Rohde - Causal Inference is Inference - A beautifully simple idea that not everyone accepts1:08:40David Rohde - Causal Inference is Inference - A beautifully simple idea that not everyone accepts
David Rohde - Causal Inference is Inference - A beautifully simple idea that not everyone accepts
zhlédnutí 759Před 2 lety
David Rohde - Causal Inference is Inference - A beautifully simple idea that not everyone accepts
Fan Li - Propensity score in Bayesian causal inference: why, why not, and how?1:02:09Fan Li - Propensity score in Bayesian causal inference: why, why not, and how?
Fan Li - Propensity score in Bayesian causal inference: why, why not, and how?
zhlédnutí 1,2KPřed 2 lety
Fan Li - Propensity score in Bayesian causal inference: why, why not, and how?
Criteo's privacy preserving ML competition - 3th Place sales leaderboard12:42Criteo's privacy preserving ML competition - 3th Place sales leaderboard
Criteo's privacy preserving ML competition - 3th Place sales leaderboard
zhlédnutí 147Před 2 lety
Criteo's privacy preserving ML competition - 3th Place sales leaderboard
Criteo's privacy preserving ML competition - 3nd Place (2nd place on sales)14:46Criteo's privacy preserving ML competition - 3nd Place (2nd place on sales)
Criteo's privacy preserving ML competition - 3nd Place (2nd place on sales)
zhlédnutí 144Před 2 lety
Criteo's privacy preserving ML competition - 3nd Place (2nd place on sales)
Criteo's privacy preserving ML competition - 1st Place11:49Criteo's privacy preserving ML competition - 1st Place
Criteo's privacy preserving ML competition - 1st Place
zhlédnutí 488Před 2 lety
Criteo's privacy preserving ML competition - 1st Place
Criteo's privacy preserving ML competition - 2nd place clicks presentation18:50Criteo's privacy preserving ML competition - 2nd place clicks presentation
Criteo's privacy preserving ML competition - 2nd place clicks presentation
zhlédnutí 340Před 2 lety
Criteo's privacy preserving ML competition - 2nd place clicks presentation
Dynamical state-space models for videos: stochastic prediction and spatio-temporal disentanglement1:09:59Dynamical state-space models for videos: stochastic prediction and spatio-temporal disentanglement
Dynamical state-space models for videos: stochastic prediction and spatio-temporal disentanglement
zhlédnutí 302Před 3 lety
Dynamical state-space models for videos: stochastic prediction and spatio-temporal disentanglement
Kernel matrices in the flat limit1:04:39Kernel matrices in the flat limit
Kernel matrices in the flat limit
zhlédnutí 140Před 3 lety
Kernel matrices in the flat limit
Automatic Backward Filtering Forward Guiding for Markov processes and graphical models1:06:23Automatic Backward Filtering Forward Guiding for Markov processes and graphical models
Automatic Backward Filtering Forward Guiding for Markov processes and graphical models
zhlédnutí 404Před 3 lety
Automatic Backward Filtering Forward Guiding for Markov processes and graphical models
Monte Carlo integration with repulsive point processes1:01:58Monte Carlo integration with repulsive point processes
Monte Carlo integration with repulsive point processes
zhlédnutí 230Před 3 lety
Monte Carlo integration with repulsive point processes
A general perspective on the Metropolis-Hastings kernel - Part 21:02:38A general perspective on the Metropolis-Hastings kernel - Part 2
A general perspective on the Metropolis-Hastings kernel - Part 2
zhlédnutí 191Před 3 lety
A general perspective on the Metropolis-Hastings kernel - Part 2
A general perspective on the Metropolis-Hastings kernel - Part 11:09:36A general perspective on the Metropolis-Hastings kernel - Part 1
A general perspective on the Metropolis-Hastings kernel - Part 1
zhlédnutí 441Před 3 lety
A general perspective on the Metropolis-Hastings kernel - Part 1
Approximate Bayesian computation with surrogate posteriors1:01:22Approximate Bayesian computation with surrogate posteriors
Approximate Bayesian computation with surrogate posteriors
zhlédnutí 296Před 3 lety
Approximate Bayesian computation with surrogate posteriors
Backfitting for large scale crossed random effects regressions57:25Backfitting for large scale crossed random effects regressions
Backfitting for large scale crossed random effects regressions
zhlédnutí 375Před 3 lety
Backfitting for large scale crossed random effects regressions

Komentáře

  • @gvpathi
    @gvpathi Před měsícem

    Stamped with your presentation skill. All clear and lucid and 100 slides. 🎉❤🎉

  • @petegranneman1623
    @petegranneman1623 Před měsícem

    Great Presentation... RIP TD Ameritrade

  • @gamuchiraindawana2827
    @gamuchiraindawana2827 Před 6 měsíci

    I've never thought about "no free lunch" the way he explained it, that there's always a price to pay in the form of a tradeoff, when you gain performance here you're likely loosing something else there. I always looked at it from the perspective that you can't just blindly apply a model on a dataset and expect the model to do all the work for you without any more input from you.

  • @nocopyrightgameplaystockvi231
    @nocopyrightgameplaystockvi231 Před 8 měsíci

    The legend

  • @rjendoubi
    @rjendoubi Před 9 měsíci

    Great presentation. Need to check those tips about SORT BY are in the Impala Cookbook 🙂 Would love to see an updated presentation like this. Thanks Mostafa!

  • @MikeVanMeter-ih8uo
    @MikeVanMeter-ih8uo Před 10 měsíci

    Your voice is sexy

  • @curtis1732
    @curtis1732 Před 11 měsíci

    *Promo SM*

  • @thebicycleman8062
    @thebicycleman8062 Před 11 měsíci

    I like how the word MOAR is the most ENLARGED TEXT lollll

  • @thebicycleman8062
    @thebicycleman8062 Před 11 měsíci

    we need MOAR talks like this! amazing!

  • @allanledner
    @allanledner Před rokem

    😠 *promo sm*

  • @muntedme203
    @muntedme203 Před rokem

    Sounds cool

  • @hr3nk
    @hr3nk Před rokem

    Very informative talk, I wonder if newer Transformer based models have been applied to sequential recommendations task (I've seen some papers but not public talks), would really appreciate if anybody shared ☺

  • @m.almansoori9726
    @m.almansoori9726 Před rokem

    Great presentation; is it possible to implement it in sequence log data clustering?

    • @criteoeng
      @criteoeng Před rokem

      Hello, we would advise reaching out to the speaker, Sean Law, directly.

  • @manojyadav-ej6kz
    @manojyadav-ej6kz Před rokem

    Can I get more information on this ...

    • @criteoeng
      @criteoeng Před rokem

      Hello Manoj, Should you wish for more information, we advise you to reach out to Alexandros Karatzoglou directly.

    • @manojyadav-ej6kz
      @manojyadav-ej6kz Před rokem

      @@criteoeng can you pls provide any email or other mode to contact Alex

    • @criteoeng
      @criteoeng Před rokem

      @@manojyadav-ej6kz He is reachable through his LinkedIn: linkedin.com/in/alexandroskaratzoglou or at alexkz@google.com

  • @juanotavalo
    @juanotavalo Před rokem

    Very clear explanation, I'm not a native english speaker but I understood everything clearly.

  • @alexfernandohuenten1374
    @alexfernandohuenten1374 Před rokem

    Awesome

  • @noumantelusko1722
    @noumantelusko1722 Před rokem

    nice explanation and great work, may be this is what me and my team were looking for thanks man!

  • @wellitongomes9250
    @wellitongomes9250 Před 2 lety

    Olá, gostaria de saber se a Criteo trabalha no Brasil, usando plataforma de marketing digital, eu estou fazendo parte de uma plataforma que usa nome da criteo, porém estou com dúvida se realmente é da Criteo. está plataforma libera 50 anúncios para nós divulgar na rede. e os ganhos são em dólares.

    • @criteoeng
      @criteoeng Před 2 lety

      Olá, Obrigado pelo contato. Você poderia, por favor, enviar sua dúvida e contato para MMSBRManagers@criteo.com . Obrigado! Criteo

  • @lfmtube
    @lfmtube Před 2 lety

    Great Video and better than great even explained! Thanks

  • @luckhuc7968
    @luckhuc7968 Před 2 lety

    The video sound is pretty good, beyond my imagination

  • @shreyas9312
    @shreyas9312 Před 2 lety

    at 15:50 the matrix profile looks like it is not plotted as is - based on the second subplot, the Y axis is between 0.5 and 2.5 whereas the matrix profile has values ranging from 1.4 to 14.1- what kind of processing has been done on the matrix profile before plotting it?

  • @williamkirwin6438
    @williamkirwin6438 Před 2 lety

    Super insightful!

  • @adityateja9900
    @adityateja9900 Před 3 lety

    16:22 .. I thought that guy was asleep lol

  • @mathandsciencereboot2662
    @mathandsciencereboot2662 Před 3 lety

    Can this be done using SPSS?

  • @PrabhatKumar-fn4vy
    @PrabhatKumar-fn4vy Před 3 lety

    Your book is awesome everyone is talking about that book

  • @soonpaomeng
    @soonpaomeng Před 3 lety

    Hope u earn 2000 pips a day

    • @johnny2bi4
      @johnny2bi4 Před 3 lety

      does it work for trading?

    • @soonpaomeng
      @soonpaomeng Před 3 lety

      @@johnny2bi4 Seasonal for sure, season maybe too short, life span is key

    • @johnny2bi4
      @johnny2bi4 Před 3 lety

      @@soonpaomeng definitely I'm looking are predicting the next few candles that's the goal.

    • @soonpaomeng
      @soonpaomeng Před 3 lety

      @@johnny2bi4 that's almost impossible

    • @johnny2bi4
      @johnny2bi4 Před 3 lety

      Pao Meng Soon what’s more feasible ?

  • @vishalpandey2921
    @vishalpandey2921 Před 3 lety

    robust approach simplified.

  • @ronniegrimes6535
    @ronniegrimes6535 Před 3 lety

    Thanks God

  • @ronniegrimes6535
    @ronniegrimes6535 Před 3 lety

    Doneanotherartsdotsnotsdotsdots

  • @myronwoods40
    @myronwoods40 Před 4 lety

    13:45 Did the cameraman intentionally zoom in on that guy sleeping??

  • @PallatiCharan
    @PallatiCharan Před 4 lety

    This is the best and easy way to find an anomalies but it's effective thanks Sean law introducing open source library stumpy

  • @gryshakov
    @gryshakov Před 4 lety

    33:45 now that basically tells everything about this lecture

    • @RandallLewis
      @RandallLewis Před 2 lety

      LoL. What an excellent cut to the audience! I was falling asleep during this conference, too, due to jetlag! 😴

    • @ResilientFighter
      @ResilientFighter Před rokem

      i was thinking more 15:22

  • @bhawnadixit3138
    @bhawnadixit3138 Před 4 lety

    Thank you for explaining it well. I was searching for something with respect to biological data and may be I can use it. Great talk..

  • @kennykobau
    @kennykobau Před 4 lety

    Internal Data University is for Spotify employees? If not, how do I apply?

  • @BabjiEManohar
    @BabjiEManohar Před 5 lety

    wtf is this ? where to look at the slide? whole point of video is lost.... shit..

  • @bibekdahal3752
    @bibekdahal3752 Před 5 lety

    This guy knows what he is talking. However, his audience there and me be like, wtf is this.

  • @vikahoha6051
    @vikahoha6051 Před 5 lety

    Какой хороший, съела бы зацёмкала

  • @gounna1795
    @gounna1795 Před 6 lety

    11:50 The great engineer asks us to click star at github. It will make his day :) github.com/spotify/scio

  • @darthyzhu5767
    @darthyzhu5767 Před 7 lety

    Great talk! wonder where to have a look at the slides.

    • @zeta-man
      @zeta-man Před 5 lety

      forget the slides, download the complete book from him on Causal Inference it's published as open access titles by MIT mitpress.mit.edu/books/elements-causal-inference