NABD Conf 2018 - The conference by developers for developers
New Your favorite anti-conference is back in Ann Arbor in fall 2020! There are lots of conferences these days and almost all of them promise new and magical insights that will surely revolutionize the way you work. This is not one of them. NABD’s main conference is first and foremost about engineers solving problems and sharing those resolutions with others–and we encourage our speakers to share t
KDD2014_study
KDD 2014勉強会資料 Modeling delayed feedback in display advertisingRead less
Parquet, Hive and Criteo: the Backstory - Criteo Engineering
About a year ago I attended the Paris Hadoop Users Group (HUG) to listen to Marcel Kornacker discuss Impala, Cloudera’s version of Dremel and along with it a new HDFS file format, Parquet. The talk was great–Impala promised great improvements in query times on HDFS and Parquet was to be its native storage format but actually be execution engine agnostic, meaning that in theory it would be easy to
Display Advertising Challenge | Kaggle
Predict click-through rates on display ads
Response prediction for display advertising - WSDM 2014
The document discusses techniques for improving ad click prediction, a crucial task for online advertising. It presents the FTRL-Proximal learning algorithm, which combines the accuracy of online gradient descent with the sparsity of regularized dual averaging. Memory saving techniques are also key, including probabilistic feature inclusion, subsampling training data, and encoding values with fewe
Chapelle's Tech Tips
Oliver Chapelle is the creative mind behind the popular lifehacks blog that bears his name. As a seasoned copyrighter, he has a knack for crafting engaging content that simplifies everyday tasks and helps readers optimize their lives. With a natural curiosity and a passion for problem-solving, Oliver is constantly on the lookout for innovative tips and tricks to share with his audience. He believe
Criteo hadoop based architecture - and maybe storm and kakfa in the future - Mathieu ELIE
French article about how criteo use hadoop for its targeting platform. I give you a resume. Les coulisses informatiques de Criteo – Web & Tech [space height=”30″] goal: publish the best ads from visitors datas of the ads network big data to analyse : hadoop is there 7 data centers ! data input : customer site vistors infos enrich data over and over to build visitor profiles output : show the most
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From Just a Bunch of Engineers to Data Reliability Engineering - Criteo Engineering
Real time metrics on tracker calls
Using Hive for Mahout Experimentation
The Commerce Media Platform for the Open Internet | Criteo