Linking pages
Linked pages
- Pi Day - Wikipedia http://en.wikipedia.org/wiki/pi_day 213 comments
- Kaggle: Your Machine Learning and Data Science Community http://www.kaggle.com 204 comments
- Microsoft – Cloud, Computers, Apps & Gaming http://www.microsoft.com/en-us/default.aspx 66 comments
- GitHub - szilard/benchm-ml: A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.). https://github.com/szilard/benchm-ml 34 comments
- Disqus – The #1 way to build your audience https://disqus.com 32 comments
- Artificial neural network - Wikipedia https://en.wikipedia.org/wiki/artificial_neural_network 27 comments
- Black box - Wikipedia https://en.wikipedia.org/wiki/Black_box 13 comments
- Pearson correlation coefficient - Wikipedia https://en.wikipedia.org/wiki/Pearson_correlation_coefficient 11 comments
- GitHub - microsoft/LightGBM: A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. https://github.com/Microsoft/LightGBM 11 comments
- http://r-statistics.co/assumptions-of-linear-regression.html 11 comments
- Mapping Where Arrests Frequently Occur in San Francisco Using Crime Data | Max Woolf's Blog http://minimaxir.com/2015/12/sf-arrest-maps/ 6 comments
- Hierarchical clustering - Wikipedia https://en.wikipedia.org/wiki/Hierarchical_clustering 6 comments
- DataSF | San Francisco Open Data https://data.sfgov.org/ 5 comments
- San Francisco Crime Classification | Kaggle https://www.kaggle.com/c/sf-crime 5 comments
- Analyzing San Francisco Crime Data to Determine When Arrests Frequently Occur | Max Woolf's Blog http://minimaxir.com/2015/12/sf-arrests/ 3 comments
- scikit-learn: machine learning in Python — scikit-learn 1.3.1 documentation http://scikit-learn.org/stable/index.html 1 comment
- H2O.ai | The fastest, most accurate AI Cloud Platform https://h2o.ai/ 1 comment
- GitHub - dmlc/xgboost: Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow https://github.com/dmlc/xgboost 0 comments
- One-hot - Wikipedia https://en.wikipedia.org/wiki/One-hot 0 comments
- https://www.twitch.tv/minimaxir 0 comments
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