ivanliu1989 / Predict-click-through-rates-on-display-ads
Display advertising is a billion dollar effort and one of the central uses of machine learning on the Internet. However, its data and methods are usually kept under lock and key. In this research competition, CriteoLabs is sharing a week’s worth of data for you to develop models predicting ad click-through rate (CTR). Given a user and the page h…
☆17Updated 5 years ago
Alternatives and similar repositories for Predict-click-through-rates-on-display-ads:
Users that are interested in Predict-click-through-rates-on-display-ads are comparing it to the libraries listed below
- iCQA - Intelligent Community Question Answering Framework☆31Updated 8 years ago
- k-means + a linear model = good results☆55Updated 10 years ago
- Predicting job salaries from ads - a Kaggle competition☆55Updated 10 years ago
- Recommendations Serving Engine using python☆28Updated 9 years ago
- Real Time Bidding Algorithm Implementation☆38Updated 10 years ago
- Model for the Event Recommendation Engine Challenge on Kaggle.com☆42Updated 12 years ago
- Mercury：Recommendation Engine Sandbox Using Movielens Dataset☆8Updated 10 years ago
- An LSTM based query classification for Mandrain, implemented using Tensorflow☆19Updated 8 years ago
- A set of methods that predict the future values of popularity indices for news posts using a variety of features.☆33Updated 7 years ago
- tag doc using topN words with lda☆10Updated 9 years ago
- Code for Kaggle's Default Loan Prediction - Imperial College London challenge.☆29Updated 10 years ago
- Click Through Rate Prediction☆14Updated 10 years ago
- Deep Learning Recommender System☆53Updated 8 years ago
- Automated NLP sentiment predictions- batteries included, or use your own data☆18Updated 7 years ago
- Film recommendations with Apache Spark and Python☆61Updated 9 years ago
- Different approaches to computing document similarity☆28Updated 8 years ago
- Kaggle Avazu beat-the-benchmark model☆36Updated 10 years ago
- Using gbdt+lr in recommend system and comparing the auc of lr, gbdt, gbdt+lr.☆24Updated 7 years ago
- Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world…☆127Updated 11 years ago
- Pylearn2 in practice☆41Updated 10 years ago
- Experiment on text summarization techniques and exploring Tensorflow.☆15Updated 7 years ago
- Theano based deep ANN learning code☆38Updated 14 years ago
- Source code for exploring MLlib blog post☆11Updated 9 years ago
- feng - feature engineering for machine-learning champions☆27Updated 7 years ago
- Content based Recommender System which implements sentiment analysis(Naive Bayes,SVMs) on Amazon product reviews. Built in Python(Beautif…☆10Updated 10 years ago
- a large scale lbfgs using a method in nips 2014 paper "Large-scale L-BFGS using MapReduce".☆13Updated 9 years ago
- MXNet for CTR☆50Updated 7 years ago
- Homebrew implementation of IBM Watson DeepQA (NLTK, Semantic Web, AI strategies)☆16Updated 13 years ago
- My capstone project for Galvanize (Zipfian Academy)☆38Updated 6 years ago
- TalkingData AdTracking Fraud Detection Challenge on Kaggle Competition☆13Updated 6 years ago