Mark Conway

11 Abonné

I lead the development and deployment of scaleable models, with expertise in both real-time and big data architecture. = Apache: Spark, Hadoop, Pig, Hive, and Oozie. = Python: scikit-learn, pandas, NumPy, and Luigi. = R: PivotalR, madlib, Time Series Analysis with X12-ARIMA. = Modeling: MLLib, H2O, yhat, Sense = Machine Learning: Random Forests, Clustering, Association Rules, and Logistic Regression. = Software Development: Streaming, Distributed Systems, REST APIs. = Visualization: Matplotlib, ggplot2, Seaborn, and D3. = Database: Hive, Postgres, SQL I build data science pipelines and frameworks (see my presentations below).

model classification machine learning kaggle predictive analytics analytics data science software scikit-learn logistic regression xgboost tensorflow pipeline pandas python gradient boosting random forest framework stock market regression market analysis change point nfl fantasy sports

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Mark Conway

Présentations

Sports Analytics

Change Point Analysis

AlphaPy: A Data Science Pipeline in Python

J’aime

AlphaPy

kaggle_meet_up

Kaggle Winning Solution Xgboost algorithm -- Let us learn from its author

General Tips for participating Kaggle Competitions