Repository: spark-website Updated Branches: refs/heads/asf-site 46fb65a40 -> 62155dfa6
Fix a few bugs in the release notes. Project: http://git-wip-us.apache.org/repos/asf/spark-website/repo Commit: http://git-wip-us.apache.org/repos/asf/spark-website/commit/62155dfa Tree: http://git-wip-us.apache.org/repos/asf/spark-website/tree/62155dfa Diff: http://git-wip-us.apache.org/repos/asf/spark-website/diff/62155dfa Branch: refs/heads/asf-site Commit: 62155dfa62bc83674f4b34ee0f8299940e6311ed Parents: 46fb65a Author: Reynold Xin <r...@databricks.com> Authored: Wed Jul 27 10:01:27 2016 -0700 Committer: Reynold Xin <r...@databricks.com> Committed: Wed Jul 27 10:01:27 2016 -0700 ---------------------------------------------------------------------- releases/_posts/2016-07-26-spark-release-2-0-0.md | 8 ++++---- site/releases/spark-release-2-0-0.html | 6 +++--- 2 files changed, 7 insertions(+), 7 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark-website/blob/62155dfa/releases/_posts/2016-07-26-spark-release-2-0-0.md ---------------------------------------------------------------------- diff --git a/releases/_posts/2016-07-26-spark-release-2-0-0.md b/releases/_posts/2016-07-26-spark-release-2-0-0.md index 1cc5cdd..ab19aa3 100644 --- a/releases/_posts/2016-07-26-spark-release-2-0-0.md +++ b/releases/_posts/2016-07-26-spark-release-2-0-0.md @@ -73,16 +73,16 @@ In addition, when building without Hive support, Spark SQL should have almost al ### MLlib -The DataFrame-based API is now the primary API. The RDD-based API is entering maintenance mode. See the MLlib guide for details +The DataFrame-based API is now the primary API. The RDD-based API is entering maintenance mode. See the [MLlib guide](http://spark.apache.org/docs/2.0.0/ml-guide.html) for details #### New features -- ML persistence: The DataFrames-based API provides near-complete support for saving and loading ML models and Pipelines in Scala, Java, Python, and R. See this blog post for details. (SPARK-6725, SPARK-11939, SPARK-14311) -- MLlib in R: SparkR now offers MLlib APIs for generalized linear models, naive Bayes, k-means clustering, and survival regression. See this talk to learn more. +- ML persistence: The DataFrames-based API provides near-complete support for saving and loading ML models and Pipelines in Scala, Java, Python, and R. See this [blog post](https://databricks.com/blog/2016/05/31/apache-spark-2-0-preview-machine-learning-model-persistence.html) and the following JIRAs for details: SPARK-6725, SPARK-11939, SPARK-14311. +- MLlib in R: SparkR now offers MLlib APIs for generalized linear models, naive Bayes, k-means clustering, and survival regression. See [this talk](https://spark-summit.org/2016/events/recent-developments-in-sparkr-for-advanced-analytics/) to learn more. - Python: PySpark now offers many more MLlib algorithms, including LDA, Gaussian Mixture Model, Generalized Linear Regression, and more. - Algorithms added to DataFrames-based API: Bisecting K-Means clustering, Gaussian Mixture Model, MaxAbsScaler feature transformer. -This talk lists many of these new features. +[This talk](https://spark-summit.org/2016/events/apache-spark-mllib-20-preview-data-science-and-production/) lists many of these new features. #### Speed/scaling Vectors and Matrices stored in DataFrames now use much more efficient serialization, reducing overhead in calling MLlib algorithms. (SPARK-14850) http://git-wip-us.apache.org/repos/asf/spark-website/blob/62155dfa/site/releases/spark-release-2-0-0.html ---------------------------------------------------------------------- diff --git a/site/releases/spark-release-2-0-0.html b/site/releases/spark-release-2-0-0.html index 66ca23b..83f949a 100644 --- a/site/releases/spark-release-2-0-0.html +++ b/site/releases/spark-release-2-0-0.html @@ -282,13 +282,13 @@ <h4 id="new-features-1">New features</h4> <ul> - <li>ML persistence: The DataFrames-based API provides near-complete support for saving and loading ML models and Pipelines in Scala, Java, Python, and R. See this blog post for details. (SPARK-6725, SPARK-11939, SPARK-14311)</li> - <li>MLlib in R: SparkR now offers MLlib APIs for generalized linear models, naive Bayes, k-means clustering, and survival regression. See this talk to learn more.</li> + <li>ML persistence: The DataFrames-based API provides near-complete support for saving and loading ML models and Pipelines in Scala, Java, Python, and R. See this <a href="https://databricks.com/blog/2016/05/31/apache-spark-2-0-preview-machine-learning-model-persistence.html";>blog post</a> and the following JIRAs for details: SPARK-6725, SPARK-11939, SPARK-14311.</li> + <li>MLlib in R: SparkR now offers MLlib APIs for generalized linear models, naive Bayes, k-means clustering, and survival regression. See <a href="https://spark-summit.org/2016/events/recent-developments-in-sparkr-for-advanced-analytics/";>this talk</a> to learn more.</li> <li>Python: PySpark now offers many more MLlib algorithms, including LDA, Gaussian Mixture Model, Generalized Linear Regression, and more.</li> <li>Algorithms added to DataFrames-based API: Bisecting K-Means clustering, Gaussian Mixture Model, MaxAbsScaler feature transformer.</li> </ul> -<p>This talk lists many of these new features.</p> +<p><a href="https://spark-summit.org/2016/events/apache-spark-mllib-20-preview-data-science-and-production/";>This talk</a> lists many of these new features.</p> <h4 id="speedscaling">Speed/scaling</h4> <p>Vectors and Matrices stored in DataFrames now use much more efficient serialization, reducing overhead in calling MLlib algorithms. (SPARK-14850)</p> --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
